Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

/pdf/integrative-genomics-viewer-b637hdfl11.pdf

Integrative genomics viewer

Background Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples. Methods To examine intratumor heterogeneity, we performed exome sequencing, chromosome aberration analysis, and ploidy profiling on multiple spatially separated samples obtained from primary renal carcinomas and associated metastatic sites. We characterized the consequences of intratumor heterogeneity using immunohistochemical analysis, mutation functional analysis, and profiling of messenger RNA expression. Results Phylogenetic reconstruction revealed branched evolutionary tumor growth, with 63 to 69% of all somatic mutations not detectable across every tumor region. Intratumor heterogeneity was observed for a mutation within an autoinhibitory domain of the mammalian target of rapamycin (mTOR) kinase, correlating with S6 and 4EBP phosphorylation in vivo and constitutive activation of mTOR kinase activity in vitro. Mutational intratumor heterogeneity was seen for multiple tumor-suppressor genes converging on loss of function; SETD2, PTEN, and KDM5C underwent multiple distinct and spatially separated inactivating mutations within a single tumor, suggesting convergent phenotypic evolution. Gene-expression signatures of good and poor prognosis were detected in different regions of the same tumor. Allelic composition and ploidy profiling analysis revealed extensive intratumor heterogeneity, with 26 of 30 tumor samples from four tumors harboring divergent allelic-imbalance profiles and with ploidy heterogeneity in two of four tumors. Conclusions Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development. Intratumor heterogeneity, associated with heterogeneous protein function, may foster tumor adaptation and therapeutic failure through Darwinian selection. (Funded by the Medical Research Council and others.)

http://www.therenegadecell.com/wiki/images/0/0d/NEJM-2012-366%2810%29-883.pdf

Intratumor heterogeneity and branched evolution revealed by multiregion sequencing.

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

https://www.cell.com/cell/pdf/S0092-8674(09)00083-X.pdf

Origins and Mechanisms of miRNAs and siRNAs

Background: MicroRNAs (miRNAs) are small (~19-24nt) non-coding RNAs that play important roles in various biological processes. To date, the next-generation sequencing (NGS) technology has been widely used to discover miRNAs in plants and animals. Although evolutionary analysis is important to reveal the functional dynamics of miRNAs, few computational tools have been developed to analyze the evolution of miRNA sequence and expression across species, especially the newly emerged ones, Results: We developed miREvo, an integrated software platform with a graphical user interface (GUI), to process deep-sequencing data of small RNAs and to analyze miRNA sequence and expression evolution based on the multiple-species whole genome alignments (WGAs). Three major features are provided by miREvo: (i) to identify novel miRNAs in both plants and animals, based on a modified miRDeep algorithm, (ii) to detect miRNA homologs and measure their pairwise evolutionary distances among multiple species based on a WGA, and (iii) to profile miRNA expression abundances and analyze expression divergence across multiple species (small RNA libraries). Moreover, we demonstrated the utility of miREvo with Illumina data sets from Drosophila melanogaster and Arabidopsis, respectively. Conclusion: This work presents an integrated pipline, miREvo, for exploring the expressional and evolutionary dynamics of miRNAs across multiple species. MiREvo is standalone, modular, and freely available at http://evolution. sysu.edu.cn/software/mirevo.htm under the GNU/GPL license.

/pdf/mirevo-an-integrative-microrna-evolutionary-analysis-3ihlrw5i9e.pdf

miREvo: an integrative microRNA evolutionary analysis platform for next-generation sequencing experiments

By comparing the low-, intermediate-, and high-frequency parts of the frequency spectrum, we gain information on the evolutionary forces that influence the pattern of polymorphism in population samples We emphasize the high-frequency variants on which positive selection and negative (background) selection exhibit different effects We propose a new estimator of θ (the product of effective population size and neutral mutation rate), θ L , which is sensitive to the changes in high-frequency variants The new θ L allows us to revise Fay and Wu's H -test by normalization To complement the existing statistics (the H -test and Tajima's D -test), we propose a new test, E , which relies on the difference between θ L and Watterson's θW We show that this test is most powerful in detecting the recovery phase after the loss of genetic diversity, which includes the postselective sweep phase The sensitivities of these tests to (or robustness against) background selection and demographic changes are also considered Overall, D and H in combination can be most effective in detecting positive selection while being insensitive to other perturbations We thus propose a joint test, referred to as the DH test Simulations indicate that DH is indeed sensitive primarily to directional selection and no other driving forces

https://www.genetics.org/content/genetics/174/3/1431.full.pdf

Statistical Tests for Detecting Positive Selection by Utilizing High-Frequency Variants

MicroRNAs (miRNAs) are small, endogenously expressed RNAs that regulate mRNAs post-transcriptionally. The class of miRNA genes, like other gene classes, should experience birth, death and persistence of its members. We carried out deep sequencing of miRNAs from three species of Drosophila, and obtained 107,000 sequences that map to no fewer than 300 loci that were not previously known. We observe a large class of miRNA genes that are evolutionarily young, with a rate of birth of 12 new genes per million years (Myr). Most of these new miRNAs originated from non-miRNA sequences. Among the new genes, we estimate that 96% disappeared quickly in the course of evolution; only 4% of new miRNA genes were retained by natural selection. Furthermore, only 60% of these retained genes became integrated into the transcriptome in the long run (60 Myr). This small fraction (2.5%) of surviving miRNAs may later on become moderately or highly expressed. Our results suggest that there is a high birth rate of new miRNA genes, accompanied by a comparably high death rate. The estimated net gain of long-lived miRNA genes, which is not strongly affected by either the depth or the breadth (number of tissues) of sequencing, is 0.3 genes per Myr in Drosophila.

The birth and death of microRNA genes in Drosophila

The accumulation of deleterious mutations in rice genomes: a hypothesis on the cost of domestication.

Genealogical patterns in different genomic regions may be different due to the joint influence of gene flow and selection. The existence of two subspecies of cultivated rice provides a unique opportunity for analyzing these effects during domestication. We chose 66 accessions from the three rice taxa (about 22 each from Oryza sativa indica, O. sativa japonica, and O. rufipogon) for whole-genome sequencing. In the search for the signature of selection, we focus on low diversity regions (LDRs) shared by both cultivars. We found that the genealogical histories of these overlapping LDRs are distinct from the genomic background. While indica and japonica genomes generally appear to be of independent origin, many overlapping LDRs may have originated only once, as a result of selection and subsequent introgression. Interestingly, many such LDRs contain only one candidate gene of rice domestication, and several known domestication genes have indeed been “rediscovered” by this approach. In summary, we identified 13 additional candidate genes of domestication.

/pdf/two-evolutionary-histories-in-the-genome-of-rice-the-roles-3zs765pdk1.pdf

Suhua Shi

Papers

miREvo: an integrative microRNA evolutionary analysis platform for next-generation sequencing experiments

Statistical Tests for Detecting Positive Selection by Utilizing High-Frequency Variants

The birth and death of microRNA genes in Drosophila

The accumulation of deleterious mutations in rice genomes: a hypothesis on the cost of domestication.

Two Evolutionary Histories in the Genome of Rice: the Roles of Domestication Genes