Genomic insights into positive selection

The traditional way of identifying targets of adaptive evolution has been to study a few loci that one hypothesizes a priori to have been under selection. This approach is complicated because of the confounding effects that population demographic history and selection have on patterns of DNA sequence variation. In principle, multilocus analyses can facilitate robust inferences of selection at individual loci. The deluge of large-scale catalogs of genetic variation has stimulated many genome-wide scans for positive selection in several species. Here, we review some of the salient observations of these studies, identify important challenges ahead, consider the limitations of genome-wide scans for selection and discuss the potential significance of a comprehensive understanding of genomic patterns of selection for disease-related research.     

Hitchhiking under positive Darwinian selection

Positive selection can be inferred from its effect on linked neutral variation. In the restrictive case when there is no recombination, all linked variation is removed. If recombination is present but rare, both deterministic and stochastic models of positive selection show that linked variation hitchhikes to either low or high frequencies. While the frequency distribution of variation can be influenced by a number of evolutionary processes, an excess of derived variants at high frequency is a unique pattern produced by hitchhiking (derived refers to the nonancestral state as determined from an outgroup). We adopt a statistic, H, to measure an excess of high compared to intermediate frequency variants. Only a few high-frequency variants are needed to detect hitchhiking since not many are expected under neutrality. This is of particular utility in regions of low recombination where there is not much variation and in regions of normal or high recombination, where the hitchhiking effect can be limited to a small (<1 kb) region. Application of the H test to published surveys of Drosophila variation reveals an excess of high frequency variants that are likely to have been influenced by positive selection.     

Getting a first clue about SPRED functions

Spreds form a new protein family with an N-terminal Enabled/VASP homology 1 domain (EVH1), a central c-Kit binding domain (KBD) and a C-terminal Sprouty-related domain (SPR). They are able to inhibit the Ras-ERK signalling pathway after various mitogenic stimulations. In mice, Spred proteins are identified as regulators of bone morphogenesis, hematopoietic processes, allergen-induced airway eosinophilia and hyperresponsiveness. They inhibit cell motility and metastasis and have a high potential as tumor markers and suppressors of carcinogenesis. Moreover, in vertebrates, XtSpreds help together with XtSprouty proteins to coordinate gastrulation and mesoderm specification. Here, we give an overview of this new field and summarize the domain functions, binding partners, expression patterns and the cellular localizations, regulations and functions of Spred proteins and try to give perspectives for future scientific directions.     

Revisiting the false positive rate in detecting recent positive selection

There is increasing interest in studying the molecular mechanisms of recent adaptations caused by positive selection in the genomics era. Such endeavors to detect recent positive selection, however, have been severely handicapped by false positives due to the confounding impact of demography and the population structure. To reduce false positives, it is critical to conduct a functional analysis to identify the true candidate genes/mutations from those that are filtered through neutrality tests. However, the extremely high cost of such functional analysis may restrict studies within a small number of model species. In particular, when the false positive rate of neutrality tests is high, the efficiency of the functional analysis will also be very low. Therefore, although the recent improvements have been made in the (joint) inference of demography and selection, our ultimate goal, which is to understand the mechanism of adaptation generally in a wide variety of natural populations, may not be achieved using the currently available approaches. More attention should thus be spent on the development of more reliable tests that could not only free themselves from the confounding impact of demography and the population structure but also have reasonable power to detect selection.     

Site-directed mutagenesis using positive antibiotic selection

Various mutsgenesis protocols have been established that use the hybridization of a mismatched oligonucleotide to prime DNA synthesis on an M13 phagemid template. For efficient mutagenesis, all of these methods require a means to select for the mutant strand before or during amplification in anEscherichia coli host. In the Altered Sites II protocol, the mismatched oligonucleotide and an oligonucleotide that restores antibiotic resistance to the phagemid are simultaneously hybridized to the template and coupled by DNA synthesis and ligation. The restored antibiotic resistance is then used to select only those phagemids which incorporate the antibiotic repair oligonucleotide. Generally, between 60 and 90% of the phagemids recovered will incorporate both oligonucleotides. This method provides a simple an efficient technique for introducing specific mutations into DNA.     

Detecting amino acid sites under positive selection and purifying selection

An excess of nonsynonymous over synonymous substitution at individual amino acid sites is an important indicator that positive selection has affected the evolution of a protein between the extant sequences under study and their most recent common ancestor. Several methods exist to detect the presence, and sometimes location, of positively selected sites in alignments of protein-coding sequences. This article describes the "sitewise likelihood-ratio" (SLR) method for detecting nonneutral evolution, a statistical test that can identify sites that are unusually conserved as well as those that are unusually variable. We show that the SLR method can be more powerful than currently published methods for detecting the location of positive selection, especially in difficult cases where the strength of selection is low. The increase in power is achieved while relaxing assumptions about how the strength of selection varies over sites and without elevated rates of false-positive results that have been reported with some other methods. We also show that the SLR method performs well even under circumstances where the results from some previous methods can be misleading.     

DNA水平上检测正选择方法的研究进展

达尔文的自然选择学说指出, 自然选择作用是物种进化的主要因素。而1968年Kimura提出的中性进化学说认为中性突变和随机漂变才是进化的主要动力。在接下来的30多年时间中, 人们尝试从各种角度来检测自然选择是否存在。随着DNA测序技术的发展, 大量的DNA序列信息为检验自然选择提供了丰富的数据。因为自然选择会影响DNA变异模式, 所以可以通过分析现有的DNA样本来推断过去是否发生了自然选择。另一方面, 种群历史等因素也会影响到DNA变异模式, 因此会对自然选择的检测产生干扰。文章主要介绍了中性检验基本的概念, 全面回顾了一些经典的检验方法, 并着重介绍了近几年新发展出的研究方向。     

Detecting strong positive selection in the genome

New statistical tests have been developed in the past decade that enable us to infer evidence of recent strong positive selection from genome-wide data on single-nucleotide polymorphism and to localize the targets of selection in the genome. Based on these tests, past demographic events that led to distortions of the site-frequency spectrum of variation can be distinguished from selection, in particular if linkage disequilibrium is taken into account. These methods have been successfully applied to species from which complete sequence information and polymorphism data are available, including Drosophila melanogaster, humans, and several plant species. To make full use of the available data, however, the tests that were primarily designed for panmictic populations need to be extended to spatially structured populations.