Statistical methods for detecting molecular adaptation

By Ziheng Yang, J. Bielawski. Trends in Ecology & Evolution, 2000

1,803 citations recorded by the source corpus.

The past few years have seen the development of powerful statistical methods for detecting adaptive molecular evolution. These methods compare synonymous and nonsynonymous substitution rates in protein-coding genes, and regard a nonsynonymous rate elevated above the synonymous rate as evidence for darwinian selection. Numerous cases of molecular adaptation are being identified in various systems from viruses to humans. Although previous analyses averaging rates over sites and time have little power, recent methods designed to detect positive selection at individual sites and lineages have been successful. Here, we summarize recent statistical methods for detecting molecular adaptation, and discuss their limitations and possible improvements.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/214f82f505445ee9fadf5d9f27df6d4572079190

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Citations in the corpus

Comparing the human and chimpanzee genomes: Searching for needles in a haystack (2005, background): “this approach is generally conservative (Yang and Bielawski 2000).”
Pseudomonas genomes: diverse and adaptable. (2011, background): “Inferring lineage-specific adaptation from genome sequences The ratio of nonsynonymous to synonymous site substitutions (dN/dS) has been used to evaluate whether positive, relaxed or purifying selection is the predominant selective force on genome evolution (Yang & Bielawski, 2000).”
Nutritional evaluation of cookies produced from pigeon pea, cocoyam and sorghum flour blends (2011, background): “, 2003) often includes the search for evidence of directional selection in molecular evolution (Hsu et al., 2005; Hofmann et al., 2003; Yang and Bielawski, 2000).”
The Population Genetics of dN/dS (2008, background): “The instantaneous rate of change from codon i to codon j depends principally on the parameter v, defined as the relative rate of non-silent versus silent substitutions [2].”
Steps in the evolution of heteromorphic sex chromosomes (2005, methodology): “…loci involved, especially if several branches of a phylogenetic tree are available, so that methods such as PAML for directly detecting selection on the loci affected can be used (Yang and Bielawski, 2000), but finding good candidate loci that are potential targets of selection is very difficult.”
γ-MYN: a new algorithm for estimating Ka and Ks with consideration of variable substitution rates (2009, methodology): “Most of the methods assume simplified nucleotide substitution paths and involve ad hoc data treatments that are not well-justified [5,6].”
The rapid evolution of reproductive proteins (2002, background): “In many cases, this rapid divergence is driven by ADAPTIVE EVOLUTION (positive Darwinian selection”
DNA sequence polymorphism analysis using DnaSP. (2009, background): “There is a great variety of tests, which can be classified into different non-exclusive categories: (1) tests drawing information from synonymous non-synonymous substitutions (such as McDonald-Kreitman or dN/dS-based tests) (21, 22); (2) tests that use only polymorphism (such as Tajima or Fu and Li’”
Primary structural features of the S haplotype-specific F-box protein, SFB, in Prunus (2003, methodology): “Our methodology and nomenclature follow those of Yang and colleagues (Yang and Bielawski 2000; Yang and Swanson 2002).”
Universal Patterns of Selection in Cancer and Somatic Tissues (2018, positive): “…in the 1980s (Miyata and Yasunaga, 1980; Nei and Gojobori, 1986), it has a long history in the detection of negative and positive selection from sequencing data (Yang and Bielawski, 2000). dN/dS is particularly suitable for the analysis of coding mutations in cancer genomes, for several reasons.”