Fitness landscapes of human microsatellites.

Advances in DNA sequencing technology and computation now enable genome-wide scans for natural selection to be conducted on unprecedented scales. By examining patterns of sequence variation among individuals, biologists are identifying genes and variants that affect fitness. Despite this progress, most population genetic methods for characterizing selection assume that variants mutate in a simple manner and at a low rate.

Systematic Profiling of Short Tandem Repeats in the Cattle Genome.

Short tandem repeats (STRs), or microsatellites, are genetic variants with repetitive 2–6 base pair motifs in many mammalian genomes. Using high-throughput sequencing and experimental validations, we systematically profiled STRs in five Holsteins. We identified a total of 60,106 microsatellites and generated the first high-resolution STR map, representing a substantial pool of polymorphism in dairy cattle.

Fifteen years of genomewide scans for selection: trends, lessons and unaddressed genetic sources of complication.

Genomewide scans for natural selection (GWSS) have become increasingly common over the last 15 years due to increased availability of genome-scale genetic data. Here, we report a representative survey of GWSS from 1999 to present and find that (i) between 1999 and 2009, 35 of 49 (71%) GWSS focused on human, while from 2010 to present, only 38 of 83 (46%) of GWSS focused on human, indicating increased focus on nonmodel organisms; (ii) the large majority of GWSS incorporate interpopulation or interspecific comparisons using, for example F(ST), cross-population extended haplotype homozygosity or the ratio of nonsynonymous to synonymous substitutions; (iii) most GWSS focus on detection of directional selection rather than other modes such as balancing selection; and (iv) in human GWSS, there is a clear shift after 2004 from microsatellite markers to dense SNP data. A survey of GWSS meant to identify loci positively selected in response to severe hypoxic conditions support an approach to GWSS in which a list of a priori candidate genes based on potential selective pressures are used to filter the list of significant hits a posteriori.

The effects of microsatellite selection on linked sequence diversity.

The genome-wide scan for selection is an important method for identifying loci involved in adaptive evolution. However, theory that underlies standard scans for selection assumes a simple mutation model. In particular, recurrent mutation of the selective target is not considered.

Remarkable selective constraints on exonic dinucleotide repeats.

Long dinucleotide repeats found in exons present a substantial mutational hazard: mutations at these loci occur often and generate frameshifts. Here, we provide clear and compelling evidence that exonic dinucleotides experience strong selective constraint. In humans, only 18 exonic dinucleotides have repeat lengths greater than six, which contrasts sharply with the genome-wide distribution of dinucleotides.

Demographic history of a recent invasion of house mice on the isolated Island of Gough.

Island populations provide natural laboratories for studying key contributors to evolutionary change, including natural selection, population size and the colonization of new environments. The demographic histories of island populations can be reconstructed from patterns of genetic diversity. House mice (Mus musculus) inhabit islands throughout the globe, making them an attractive system for studying island colonization from a genetic perspective.

Genetic ancestry inference using support vector machines, and the active emergence of a unique American population.

We use genotype data from the Marshfield Clinical Research Foundation Personalized Medicine Research Project to investigate genetic similarity and divergence between Europeans and the sampled population of European Americans in Central Wisconsin, USA. To infer recent genetic ancestry of the sampled Wisconsinites, we train support vector machines (SVMs) on the positions of Europeans along top principal components (PCs). Our SVM models partition continent-wide European genetic variance into eight regional classes, which is an improvement over the geographically broader categories of recent ancestry reported by personal genomics companies.

Microsatellites as targets of natural selection.

The ability to survey polymorphism on a genomic scale has enabled genome-wide scans for the targets of natural selection. Theory that connects patterns of genetic variation to evidence of natural selection most often assumes a diallelic locus and no recurrent mutation. Although these assumptions are suitable to selection that targets single nucleotide variants, fundamentally different types of mutation generate abundant polymorphism in genomes.

A genomic portrait of human microsatellite variation.

Rapid advances in DNA sequencing and genotyping technologies are beginning to reveal the scope and pattern of human genomic variation. Although single nucleotide polymorphisms (SNPs) have been intensively studied, the extent and form of variation at other types of molecular variants remain poorly understood. Polymorphism at the most variable loci in the human genome, microsatellites, has rarely been examined on a genomic scale without the ascertainment biases that attend typical genotyping studies.

The number of alleles at a microsatellite defines the allele frequency spectrum and facilitates fast accurate estimation of theta.

Theoretical work focused on microsatellite variation has produced a number of important results, including the expected distribution of repeat sizes and the expected squared difference in repeat size between two randomly selected samples. However, closed-form expressions for the sampling distribution and frequency spectrum of microsatellite variation have not been identified. Here, we use coalescent simulations of the stepwise mutation model to develop gamma and exponential approximations of the microsatellite allele frequency spectrum, a distribution central to the description of microsatellite variation across the genome.

Activin receptor signaling regulates prostatic epithelial cell adhesion and viability.

Mutational changes coupled with endocrine, paracrine, and/or autocrine signals regulate cell division during carcinogenesis. The hormone signals remain undefined, although the absolute requirement in vitro for fetal serum indicates the necessity for a fetal serum factor(s) in cell proliferation. Using prostatic cancer cell (PCC) lines as a model of cancer cell proliferation, we have identified the fetal serum component activin A and its signaling through the activin receptor type II (ActRII), as necessary, although not sufficient, for PCC proliferation.

Copper Induces Apoptosis of Neuroblastoma Cells Via Post-translational Regulation of the Expression of Bcl-2-family Proteins and the tx Mouse is a Better Model of Hepatic than Brain Cu Toxicity.

The basic mechanism(s) by which altered Cu homeostasis is toxic to hepatocytes and neurons, the two major cell types affected in copper storage diseases such as Wilson's disease (WD), remain unclear. Using human M17 neuroblastoma cells as a model to examine Cu toxicity, we found that there was a time- and concentration-dependent induction of neuronal death, such that at 24 h there was a approximately 50 % reduction in viability with 25 muM Cu-glycine(2). Cu-glycine(2) (25:50 muM) treatment for 24 h significantly altered the expression of 296 genes, including 8 genes involved with apoptosis (BCL2-associated athanogene 3, BCL2/adenovirus E1B 19kDa interacting protein caspase 5, regulator of Fas-induced apoptosis, V-jun sarcoma virus 17 oncogene homolog, claudin 5, prostaglandin E receptor 3 and protein tyrosine phosphatase, non-receptor type 6).

Large-scale Protein-Protein Interaction prediction using novel kernel methods.

Knowledge of Protein-Protein Interactions (PPIs) can give us new insights into molecular mechanisms and properties of the cell. In this paper, we propose a novel domain-based kernel method to predict PPIs. A new kernel that measures the similarity between protein pairs based on a new feature representation is developed and applied to a large scale PPI database.

A luteinizing hormone receptor intronic variant is significantly associated with decreased risk of Alzheimer's disease in males carrying an apolipoprotein E epsilon4 allele.

Genetic and biochemical studies support the apolipoprotein E (APOE) epsilon4 allele as a major risk factor for late-onset Alzheimer's disease (AD), though ~50% of AD patients do not carry the allele. APOE transports cholesterol for luteinizing hormone (LH)-regulated steroidogenesis, and both LH and neurosteroids have been implicated in the etiology of AD. Since polymorphisms of LH beta-subunit (LHB) and its receptor (LHCGR) have not been tested for their association with AD, we scored AD and age-matched control samples for APOE genotype and 14 polymorphisms of LHB and LHCGR.

Human neurons express type I GnRH receptor and respond to GnRH I by increasing luteinizing hormone expression.

Gonadotropin-releasing hormone receptor I (GnRHR I) has been localized to the limbic system of the rat brain, although the functional consequences of GnRH signaling through these receptors is unknown. In this paper, we characterize the expression of GnRHR I in the human hippocampus and cortex, and the functionality of GnRHR I in human neuroblastoma cells. Robust GnRHR I immunoreactivity was detected in the cell body as well as along the apical dendrites of pyramidal neurons in the CA2, CA1, and end plate, but was clearly lower in the subiculum of the hippocampus.

Identification of a gonadotropin-releasing hormone receptor orthologue in Caenorhabditis elegans.

Background: The Caenorhabditis elegans genome is known to code for at least 1149 G protein-coupled receptors (GPCRs), but the GPCR(s) critical to the regulation of reproduction in this nematode are not yet known. This study examined whether GPCRs orthologous to human gonadotropin-releasing hormone receptor (GnRHR) exist in C. elegans.

Discover protein sequence signatures from protein-protein interaction data.

Background: The development of high-throughput technologies such as yeast two-hybrid systems and mass spectrometry technologies has made it possible to generate large protein-protein interaction (PPI) datasets. Mining these datasets for underlying biological knowledge has, however, remained a challenge.

Results: A total of 3108 sequence signatures were found, each of which was shared by a set of guest proteins interacting with one of 944 host proteins in Saccharomyces cerevisiae genome.