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arXiv2012

Comment on "Evidence of Abundant and Purifying Selection in Humans for Recently Acquired Regulatory Functions"

Ward and Kellis (Reports, September 5 2012) identify regulatory regions in the human genome exhibiting lineage-specific constraint and estimate the extent of purifying selection. There is no statistical rationale for the examples they highlight, and their estimates of the fraction of the genome under constraint are biased by arbitrary designations of completely constrained regions.

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arXiv2012

Zygotic combinatorial process in plants

Experimental data that prove the existence of the zygotic combinatorial process occurring in an embryogenesis-entering zygote are presented in the paper. The zygotic combinatorial process is found when analyzing F1 hybrid plants obtained from crossing homozygous forms different, minimum, in two marker enzymes, and it is found in that hybrid plant which, with one marker enzyme heterozygous spectrum, has a homozygous spectrum of the other. The zygotic combinatorial process leads to F1 hybrids uniformity aberration. The zygotic combinatory process revealed in the study is supposed to be conditioned by chromosome polyteny in mother plant cells and diminution of chromatin excess from the embryogenesis-entering zygote. An obligatory condition for combinatorial process is the presence of free exchange of cromatides among homological chromosomes in an embryogenesis-entering cell, i.e. the presence of crossing-over analogous to the one proceeding at meiosis. The found combinatorial process and the earlier-obtained data confirm the hypothesis on multi-dimensionality of inherited information coding. Differential polyteny of certain chromosome regions can lead to differences among homozygous plants having the same alleles in genes located in polytenized regions and controlling morpho-physiological traits.

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arXiv2013

Integrating Prior Knowledge Into Prognostic Biomarker Discovery based on Network Structure

Background: Predictive, stable and interpretable gene signatures are generally seen as an important step towards a better personalized medicine. During the last decade various methods have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinics is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Results: We propose a novel algorithm, called FrSVM, which integrates protein-protein interaction network information into gene selection for prognostic biomarker discovery. Our method is a simple filter based approach, which focuses on central genes with large differences in their expression. Compared to several other competing methods our algorithm reveals a significantly better prediction performance and higher signature stability. More- over, obtained gene lists are highly enriched with known disease genes and drug targets. We extendd our approach further by integrating information on candidate disease genes and targets of disease associated Transcript Factors (TFs).

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arXiv2012

Detecting gene innovations for phenotypic diversity across multiple genomes

Gene innovation is a key mechanism on the evolution and phenotypic diversity of life forms. There is a need for tools able to study gene innovation across an increasingly large number of genomic sequences to maximally capitalise our understanding of biological systems. Here we present Comparative-Phylostratigraphy, an open-source software suite that enables to time the emergence of new genes across evolutionary time and to correlate patterns of gene emergence with species traits simultaneously across whole genomes from multiple species. Such a comparative strategy is a new powerful tool for starting to dissect the relationship between gene innovation and phenotypic diversity. We describe and showcase our method by analysing recently published ant genomes. This new methodology identified significant bouts of new gene evolution in ant clades, that are associated with shifts in life-history traits. Our method allows easy integration of new genomic data as it becomes available, and thus will be a valuable analytical tool for evolutionary biologists interested in explaining the evolution of diversity of life at the level of the genes.

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arXiv2012

The GenoChip: A New Tool for Genetic Anthropology

The Genographic Project is an international effort using genetic data to chart human migratory history. The project is non-profit and non-medical, and through its Legacy Fund supports locally led efforts to preserve indigenous and traditional cultures. In its second phase, the project is focusing on markers from across the entire genome to obtain a more complete understanding of human genetic variation. Although many commercial arrays exist for genome-wide SNP genotyping, they were designed for medical genetic studies and contain medically related markers that are not appropriate for global population genetic studies. GenoChip, the Genographic Project's new genotyping array, was designed to resolve these issues and enable higher-resolution research into outstanding questions in genetic anthropology. We developed novel methods to identify AIMs and genomic regions that may be enriched with alleles shared with ancestral hominins. Overall, we collected and ascertained AIMs from over 450 populations. Containing an unprecedented number of Y-chromosomal and mtDNA SNPs and over 130,000 SNPs from the autosomes and X-chromosome, the chip was carefully vetted to avoid inclusion of medically relevant markers. The GenoChip results were successfully validated. To demonstrate its capabilities, we compared the FST distributions of GenoChip SNPs to those of two commercial arrays for three continental populations. While all arrays yielded similarly shaped (inverse J) FST distributions, the GenoChip autosomal and X-chromosomal distributions had the highest mean FST, attesting to its ability to discern subpopulations. The GenoChip is a dedicated genotyping platform for genetic anthropology and promises to be the most powerful tool available for assessing population structure and migration history.

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arXiv2012

Estimating heterozygosity from a low-coverage genome sequence, leveraging data from other individuals sequenced at the same sites

High-throughput shotgun sequence data makes it possible in principle to accurately estimate population genetic parameters without confounding by SNP ascertainment bias. One such statistic of interest is the proportion of heterozygous sites within an individual's genome, which is informative about inbreeding and effective population size. However, in many cases, the available sequence data of an individual is limited to low coverage, preventing the confident calling of genotypes necessary to directly count the proportion of heterozygous sites. Here, we present a method for estimating an individual's genome-wide rate of heterozygosity from low-coverage sequence data, without an intermediate step calling genotypes. Our method jointly learns the shared allele distribution between the individual and a panel of other individuals, together with the sequencing error distributions and the reference bias. We show our method works well, first by its performance on simulated sequence data, and secondly on real sequence data where we obtain estimates using low coverage data consistent with those from higher coverage. We apply our method to obtain estimates of the rate of heterozygosity for 11 humans from diverse world-wide populations, and through this analysis reveal the complex dependency of local sequencing coverage on the true underlying heterozygosity, which complicates the estimation of heterozygosity from sequence data. We show filters can correct for the confounding by sequencing depth. We find in practice that ratios of heterozygosity are more interpretable than absolute estimates, and show that we obtain excellent conformity of ratios of heterozygosity with previous estimates from higher coverage data.

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arXiv2012

The tectonic cause of mass extinctions and the genomic contribution to biodiversification

Despite numerous mass extinctions in the Phanerozoic eon, the overall trend in biodiversity evolution was not blocked and the life has never been wiped out. Almost all possible catastrophic events (large igneous province, asteroid impact, climate change, regression and transgression, anoxia, acidification, sudden release of methane clathrate, multi-cause etc.) have been proposed to explain the mass extinctions. However, we should, above all, clarify at what timescale and at what possible levels should we explain the mass extinction? Even though the mass extinctions occurred at short-timescale and at the species level, we reveal that their cause should be explained in a broader context at tectonic timescale and at both the molecular level and the species level. The main result in this paper is that the Phanerozoic biodiversity evolution has been explained by reconstructing the Sepkoski curve based on climatic, eustatic and genomic data. Consequently, we point out that the P-Tr extinction was caused by the tectonically originated climate instability. We also clarify that the overall trend of biodiversification originated from the underlying genome size evolution, and that the fluctuation of biodiversity originated from the interactions among the earth's spheres. The evolution at molecular level had played a significant role for the survival of life from environmental disasters.

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arXiv2012

easyGWAS: An integrated interspecies platform for performing genome-wide association studies

Motivation: The rapid growth in genome-wide association studies (GWAS) in plants and animals has brought about the need for a central resource that facilitates i) performing GWAS, ii) accessing data and results of other GWAS, and iii) enabling all users regardless of their background to exploit the latest statistical techniques without having to manage complex software and computing resources. Results: We present easyGWAS, a web platform that provides methods, tools and dynamic visualizations to perform and analyze GWAS. In addition, easyGWAS makes it simple to reproduce results of others, validate findings, and access larger sample sizes through merging of public datasets. Availability: Detailed method and data descriptions as well as tutorials are available in the supplementary materials. easyGWAS is available at http://easygwas.tuebingen.mpg.de/. Contact: dominik.grimm@tuebingen.mpg.de

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arXiv2012

A Developmental Network Theory of Gynandromorphs, Sexual Dimorphism and Species Formation

Gynandromorphs are creatures where at least two different body sections are a different sex. Bilateral gynandromorphs are half male and half female. Here we develop a theory of gynandromorph ontogeny based on developmental control networks. The theory explains the embryogenesis of all known variations of gynandromorphs found in multicellular organisms. The theory also predicts a large variety of more subtle gynandromorphic morphologies yet to be discovered. The network theory of gynandromorph development has direct relevance to understanding sexual dimorphism (differences in morphology between male and female organisms of the same species) and medical pathologies such as hemihyperplasia (asymmetric development of normally symmetric body parts in a unisexual individual). The network theory of gynandromorphs brings up fundamental open questions about developmental control in ontogeny. This in turn suggests a new theory of the origin and evolution of species that is based on cooperative interactions and conflicts between developmental control networks in the haploid genomes and epigenomes of potential sexual partners for reproduction. This network-based theory of the origin of species is a paradigmatic shift in our understanding of evolutionary processes that goes beyond gene-centered theories.

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arXiv2012

New g%AIC, g%AICc, g%BIC, and Power Divergence Fit Statistics Expose Mating between Modern Humans, Neanderthals and other Archaics

The purpose of this article is to look at how information criteria, such as AIC and BIC, relate to the g%SD fit criterion derived in Waddell et al. (2007, 2010a). The g%SD criterion measures the fit of data to model based on a normalized weighted root mean square percentage deviation between the observed data and model estimates of the data, with g%SD = 0 being a perfectly fitting model. However, this criterion may not be adjusting for the number of parameters in the model comprehensively. Thus, its relationship to more traditional measures for maximizing useful information in a model, including AIC and BIC, are examined. This results in an extended set of fit criteria including g%AIC and g%BIC. Further, a broader range of asymptotically most powerful fit criteria of the power divergence family, which includes maximum likelihood (or minimum G^2) and minimum X^2 modeling as special cases, are used to replace the sum of squares fit criterion within the g%SD criterion. Results are illustrated with a set of genetic distances looking particularly at a range of Jewish populations, plus a genomic data set that looks at how Neanderthals and Denisovans are related to each other and modern humans. Evidence that Homo erectus may have left a significant fraction of its genome within the Denisovan is shown to persist with the new modeling criteria.

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arXiv2013

Optimal Assembly for High Throughput Shotgun Sequencing

We present a framework for the design of optimal assembly algorithms for shotgun sequencing under the criterion of complete reconstruction. We derive a lower bound on the read length and the coverage depth required for reconstruction in terms of the repeat statistics of the genome. Building on earlier works, we design a de Brujin graph based assembly algorithm which can achieve very close to the lower bound for repeat statistics of a wide range of sequenced genomes, including the GAGE datasets. The results are based on a set of necessary and sufficient conditions on the DNA sequence and the reads for reconstruction. The conditions can be viewed as the shotgun sequencing analogue of Ukkonen-Pevzner's necessary and sufficient conditions for Sequencing by Hybridization.

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arXiv2013

Kerfuffle: a web tool for multi-species gene colocalization analysis

The evolutionary pressures that underlie the large-scale functional organization of the genome are not well understood in eukaryotes. Recent evidence suggests that functionally similar genes may colocalize (cluster) in the eukaryotic genome, suggesting the role of chromatin-level gene regulation in shaping the physical distribution of coordinated genes. However, few of the bioinformatic tools currently available allow for a systematic study of gene colocalization across several, evolutionarily distant species. Kerfuffle is a web tool designed to help discover, visualize, and quantify the physical organization of genomes by identifying significant gene colocalization and conservation across the assembled genomes of available species (currently up to 47, from humans to worms). Kerfuffle only requires the user to specify a list of human genes and the names of other species of interest. Without further input from the user, the software queries the e!Ensembl BioMart server to obtain positional information and discovers homology relations in all genes and species specified. Using this information, Kerfuffle performs a multi-species clustering analysis, presents downloadable lists of clustered genes, performs Monte Carlo statistical significance calculations, estimates how conserved gene clusters are across species, plots histograms and interactive graphs, allows users to save their queries, and generates a downloadable visualization of the clusters using the Circos software. These analyses may be used to further explore the functional roles of gene clusters by interrogating the enriched molecular pathways associated with each cluster.

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arXiv2013

SLiM: Simulating Evolution with Selection and Linkage

SLiM is an efficient forward population genetic simulation designed for studying the effects of linkage and selection on a chromosome-wide scale. The program can incorporate complex scenarios of demography and population substructure, various models for selection and dominance of new mutations, arbitrary gene and chromosomal structure, and user-defined recombination maps.

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arXiv2013

Anomaly Classification with the Anti-Profile Support Vector Machine

We introduce the anti-profile Support Vector Machine (apSVM) as a novel algorithm to address the anomaly classification problem, an extension of anomaly detection where the goal is to distinguish data samples from a number of anomalous and heterogeneous classes based on their pattern of deviation from a normal stable class. We show that under heterogeneity assumptions defined here that the apSVM can be solved as the dual of a standard SVM with an indirect kernel that measures similarity of anomalous samples through similarity to the stable normal class. We characterize this indirect kernel as the inner product in a Reproducing Kernel Hilbert Space between representers that are projected to the subspace spanned by the representers of the normal samples. We show by simulation and application to cancer genomics datasets that the anti-profile SVM produces classifiers that are more accurate and stable than the standard SVM in the anomaly classification setting.

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arXiv2013

An Efficient Sufficient Dimension Reduction Method for Identifying Genetic Variants of Clinical Significance

Fast and cheaper next generation sequencing technologies will generate unprecedentedly massive and highly-dimensional genomic and epigenomic variation data. In the near future, a routine part of medical record will include the sequenced genomes. A fundamental question is how to efficiently extract genomic and epigenomic variants of clinical utility which will provide information for optimal wellness and interference strategies. Traditional paradigm for identifying variants of clinical validity is to test association of the variants. However, significantly associated genetic variants may or may not be usefulness for diagnosis and prognosis of diseases. Alternative to association studies for finding genetic variants of predictive utility is to systematically search variants that contain sufficient information for phenotype prediction. To achieve this, we introduce concepts of sufficient dimension reduction and coordinate hypothesis which project the original high dimensional data to very low dimensional space while preserving all information on response phenotypes. We then formulate clinically significant genetic variant discovery problem into sparse SDR problem and develop algorithms that can select significant genetic variants from up to or even ten millions of predictors with the aid of dividing SDR for whole genome into a number of subSDR problems defined for genomic regions. The sparse SDR is in turn formulated as sparse optimal scoring problem, but with penalty which can remove row vectors from the basis matrix. To speed up computation, we develop the modified alternating direction method for multipliers to solve the sparse optimal scoring problem which can easily be implemented in parallel. To illustrate its application, the proposed method is applied to simulation data and the NHLBI's Exome Sequencing Project dataset

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arXiv2013

Preventing common hereditary disorders through time-separated twinning

Biomedical advances have led to a relaxation of natural selection in the human population in developed countries. In the absence of strong purifying selection, spontaneous and frequently deleterious mutations tend to accumulate in the human genome and gradually increase the genetic load; that is, the frequency of potentially lethal genes in the gene pool. Gradual increase in incidence of many hereditary disorders suggests deleterious impact of the genetic load on human well being. Many complex diseases such as type 1 and 2 diabetes, autism, bipolar disorder, allergies, Alzheimer disease, and some cancers show significantly higher concordance in monozygotic (MZ) twins than in dizygotic twins (DZ) or parent-child pairs, suggesting their etiology is strongly influenced by genetics. Preventing these diseases based on genetic data alone is frequently impossible. We hypothesize that the incidence of complex diseases could be significantly reduced in the future through a strategy based on time-separated twinning. This strategy involves the collection and fertilization of human oocytes followed by several rounds of artificial twinning. If preimplantation genetic screening (PGS) reports no aneuploidy or known Mendelian disorders, one of the MZ siblings would be implanted and the remaining embryos cryoconserved. Once the health of the adult MZ sibling(s) is established, subsequent parenthood with the cryoconserved twins could substantially lower the incidence of hereditary disorders with Mendelian or complex etiology. The proposed method of artificial twinning has the potential to alleviate suffering and reduce the negative social impact induced by dysgenic effects associated with known and unknown genetic factors. Time-separated twinning has the capacity to prevent further accumulation of the genetic load and to provide source of isogenic embryonic stem cells for future regenerative therapies.

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arXiv2013

Transcript length mediates developmental timing of gene expression across Drosophila

The time required to transcribe genes with long primary transcripts may limit their ability to be expressed in cells with short mitotic cycles, a phenomenon termed intron delay. As such short cycles are a hallmark of the earliest stages of insect development, we used Drosophila developmental timecourse expression data to test whether intron delay affects gene expression genome-wide, and to determine its consequences for the evolution of gene structure. We find that long zygotically expressed, but not maternally deposited, genes show substantial delay in expression relative to their shorter counterparts and that this delay persists over a substantial portion of the ~24 hours of embryogenesis. Patterns of RNA-seq coverage from the 5' and 3' ends of transcripts show that this delay is consistent with their inability to terminate transcription, but not with transcriptional initiation-based regulatory control. Highly expressed zygotic genes are subject to purifying selection to maintain compact transcribed regions, allowing conservation of embryonic expression patterns across the Drosophila phylogeny. We propose that intron delay is an underappreciated physical mechanism affecting both patterns of expression as well as gene structure of many genes across Drosophila.

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arXiv2013

Characteristics of Intronic and Intergenic Human miRNAs and Features of their Interaction with mRNA

Regulatory relationships of 686 intronic miRNA and 784 intergenic miRNAs with mRNAs of 51 intronic miRNA coding genes were established. Interaction features of studied miRNAs with 5'UTR, CDS and 3'UTR of mRNA of each gene were revealed. Functional regions of mRNA were shown to be significantly heterogenous according to the number of binding sites of miRNA and to the location density of these sites.

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