BCFtools/liftover: an accurate and comprehensive tool to convert genetic variants across genome assemblies.

MOTIVATION: Many genetics studies report results tied to genomic coordinates of a legacy genome assembly. However, as assemblies are updated and improved, researchers are faced with either realigning raw sequence data using the updated coordinate system or converting legacy datasets to the updated coordinate system to be able to combine results with newer datasets. Currently available tools to perform the conversion of genetic variants have numerous shortcomings, including poor support for indels and multi-allelic variants, that lead to a higher rate of variants being dropped or incorrectly converted. As a result, many researchers continue to work with and publish using legacy genomic coordinates. RESULTS: Here we present BCFtools/liftover, a tool to convert genomic coordinates across genome assemblies for variants encoded in the variant call format with improved support for indels represented by different reference alleles across genome assemblies and full support for multi-allelic variants. It further supports variant annotation fields updates whenever the reference allele changes across genome assemblies. The tool has the lowest rate of variants being dropped with an order of magnitude less indels dropped or incorrectly converted and is an order of magnitude faster than other tools typically used for the same task. It is particularly suited for converting variant callsets from large cohorts to novel telomere-to-telomere assemblies as well as summary statistics from genome-wide association studies tied to legacy genome assemblies. AVAILABILITY AND IMPLEMENTATION: The tool is written in C and freely available under the MIT open source license as a BCFtools plugin available at http://github.com/freeseek/score.

Comparative single-cell analysis of biopsies clarifies pathogenic mechanisms in Klinefelter syndrome.

Klinefelter syndrome (KS), also known as 47, XXY, is characterized by a distinct set of physiological abnormalities, commonly including infertility. The molecular basis for Klinefelter-related infertility is still unclear, largely because of the cellular complexity of the testis and the intricate endocrine and paracrine signaling that regulates spermatogenesis. Here, we demonstrate an analysis framework for dissecting human testis pathology that uses comparative analysis of single-cell RNA-sequencing data from the biopsies of 12 human donors. By comparing donors from a range of ages and forms of infertility, we generate gene expression signatures that characterize normal testicular function and distinguish clinically distinct forms of male infertility. Unexpectedly, we identified a subpopulation of Sertoli cells within multiple individuals with KS that lack transcription from the XIST locus, and the consequence of this is increased X-linked gene expression compared to all other KS cell populations. By systematic assessment of known cell signaling pathways, we identify 72 pathways potentially active in testis, dozens of which appear upregulated in KS. Altogether our data support a model of pathogenic changes in interstitial cells cascading from loss of X inactivation in pubertal Sertoli cells and nominate dosage-sensitive factors secreted by Sertoli cells that may contribute to the process. Our findings demonstrate the value of comparative patient analysis in mapping genetic mechanisms of disease and identify an epigenetic phenomenon in KS Sertoli cells that may prove important for understanding causes of infertility and sex chromosome evolution.

Tissue-specific DNA methylation is conserved across human, mouse, and rat, and driven by primary sequence conservation.

BACKGROUND: Uncovering mechanisms of epigenome evolution is an essential step towards understanding the evolution of different cellular phenotypes. While studies have confirmed DNA methylation as a conserved epigenetic mechanism in mammalian development, little is known about the conservation of tissue-specific genome-wide DNA methylation patterns. RESULTS: Using a comparative epigenomics approach, we identified and compared the tissue-specific DNA methylation patterns of rat against those of mouse and human across three shared tissue types. We confirmed that tissue-specific differentially methylated regions are strongly associated with tissue-specific regulatory elements. Comparisons between species revealed that at a minimum 11-37% of tissue-specific DNA methylation patterns are conserved, a phenomenon that we define as epigenetic conservation. Conserved DNA methylation is accompanied by conservation of other epigenetic marks including histone modifications. Although a significant amount of locus-specific methylation is epigenetically conserved, the majority of tissue-specific DNA methylation is not conserved across the species and tissue types that we investigated. Examination of the genetic underpinning of epigenetic conservation suggests that primary sequence conservation is a driving force behind epigenetic conservation. In contrast, evolutionary dynamics of tissue-specific DNA methylation are best explained by the maintenance or turnover of binding sites for important transcription factors. CONCLUSIONS: Our study extends the limited literature of comparative epigenomics and suggests a new paradigm for epigenetic conservation without genetic conservation through analysis of transcription factor binding sites.

The origins and functional effects of postzygotic mutations throughout the human life span.

Postzygotic mutations (PZMs) begin to accrue in the human genome immediately after fertilization, but how and when PZMs affect development and lifetime health remain unclear. To study the origins and functional consequences of PZMs, we generated a multitissue atlas of PZMs spanning 54 tissue and cell types from 948 donors. Nearly half the variation in mutation burden among tissue samples can be explained by measured technical and biological effects, and 9% can be attributed to donor-specific effects. Through phylogenetic reconstruction of PZMs, we found that their type and predicted functional impact vary during prenatal development, across tissues, and through the germ cell life cycle. Thus, methods for interpreting effects across the body and the life span are needed to fully understand the consequences of genetic variants.

Using ligand-based virtual screening to allosterically stabilize the activated state of a GPCR.

G-protein coupled receptors play an essential role in many biological processes. Despite an increase in the number of solved X-ray crystal structures of G-protein coupled receptors, capturing a G-protein coupled receptor in its activated state for structural analysis has proven to be difficult. An unexplored paradigm is stabilization of one or more conformational states of a G-protein coupled receptor via binding a small molecule to the intracellular loops. A short tetrazole peptidomimetic based on the photoactivated state of rhodopsin-bound structure of Gt(alpha)(340-350) was previously designed and shown to stabilize the photoactivated state of rhodopsin, the G-protein coupled receptor involved in vision. A pharmacophore model derived from the designed tetrazole tetrapeptide was used for ligand-based virtual screening to enhance the possible discovery of novel scaffolds. Maybridge Hitfinder and National Cancer Institute diversity libraries were screened for compounds containing the pharmacophore. Forty-seven compounds resulted from virtually screening the Maybridge library, whereas no hits resulted with the National Cancer Institute library. Three of the 47 Maybridge compounds were found to stabilize the MII state. As these compounds did not inhibit binding of transducin to photoactivated state of rhodopsin, they were assumed to be allosteric ligands. These compounds are potentially useful for crystallographic studies where complexes with these compounds might capture rhodopsin in its activated conformational state.