Reconstructing the demographic history of orang-utans using Approximate Bayesian Computation

Investigating how different evolutionary forces have shaped patterns of DNA variation within and among species requires detailed knowledge of their demographic history. Orang-utans, whose distribution is currently restricted to the South-East Asian islands of Borneo (Pongo pygmaeus) and Sumatra (Pongo abelii), have likely experienced a complex demographic history, influenced by recurrent changes in climate and sea levels, volcanic activities and anthropogenic pressures. Using the most extensive sample set of wild orang-utans to date, we employed an Approximate Bayesian Computation (ABC) approach to test the fit of 12 different demographic scenarios to the observed patterns of variation in autosomal, X-chromosomal, mitochondrial and Y-chromosomal markers. In the best-fitting model, Sumatran orang-utans exhibit a deep split of populations north and south of Lake Toba, probably caused by multiple eruptions of the Toba volcano. In addition, we found signals for a strong decline in all Sumatran populations ~24 ka, probably associated with hunting by human colonizers. In contrast, Bornean orang-utans experienced a severe bottleneck ~135 ka, followed by a population expansion and substructuring starting ~82 ka, which we link to an expansion from a glacial refugium. We showed that orang-utans went through drastic changes in population size and connectedness, caused by recurrent contraction and expansion of rainforest habitat during Pleistocene glaciations and probably hunting by early humans. Our findings emphasize the fact that important aspects of the evolutionary past of species with complex demographic histories might remain obscured when applying overly simplified models

Whole cell screen for inhibitors of pH homeostasis in Mycobacterium tuberculosis

Bacterial pathogens like Mycobacterium tuberculosis (Mtb) encounter acidic microenvironments in the host and must maintain their acid-base homeostasis to survive. A genetic screen identified two Mtb strains that cannot control intrabacterial pH (pHIB) in an acidic environment; infection with either strain led to severe attenuation in mice. To search for additional proteins that Mtb requires to survive at low pH, we introduced a whole-cell screen for compounds that disrupt pHIB, along with counter-screens that identify ionophores and membrane perturbors. Application of these methods to a natural product library identified four compounds of interest, one of which may inhibit novel pathway(s). This approach yields compounds that may lead to the identification of pathways that allow Mtb to survive in acidic environments, a setting in which Mtb is resistant to most of the drugs currently used to treat tuberculosis

UBVRI Light Curves of 44 Type Ia Supernovae

We present UBVRI photometry of 44 type-Ia supernovae (SN Ia) observed from 1997 to 2001 as part of a continuing monitoring campaign at the Fred Lawrence Whipple Observatory of the Harvard-Smithsonian Center for Astrophysics. The data set comprises 2190 observations and is the largest homogeneously observed and reduced sample of SN Ia to date, nearly doubling the number of well-observed, nearby SN Ia with published multicolor CCD light curves. The large sample of U-band photometry is a unique addition, with important connections to SN Ia observed at high redshift. The decline rate of SN Ia U-band light curves correlates well with the decline rate in other bands, as does the U-B color at maximum light. However, the U-band peak magnitudes show an increased dispersion relative to other bands even after accounting for extinction and decline rate, amounting to an additional ~40% intrinsic scatter compared to B-band.Comment: 84 authors, 71 pages, 51 tables, 10 figures. Accepted for publication in the Astronomical Journal. Version with high-res figures and electronic data at http://astron.berkeley.edu/~saurabh/cfa2snIa

Distinct genotypic profiles of the two major clades of Mycobacterium africanum

Background: Mycobacterium tuberculosis is the principal etiologic agent of human tuberculosis (TB) and a member of the M. tuberculosis complex (MTC). Additional MTC species that cause TB in humans and other mammals include Mycobacterium africanum and Mycobacterium bovis. One result of studies interrogating recently identified MTC phylogenetic markers has been the recognition of at least two distinct lineages of M. africanum, known as West African-1 and West African-2. Methods: We screened a blinded non-random set of MTC strains isolated from TB patients in Ghana (n = 47) for known chromosomal region-of-difference (RD) loci and single nucleotide polymorphisms (SNPs). A MTC PCR-typing panel, single-target standard PCR, multi-primer PCR, PCR-restriction fragment analysis, and sequence analysis of amplified products were among the methods utilized for the comparative evaluation of targets and identification systems. The MTC distributions of novel SNPs were characterized in the both the Ghana collection and two other diverse collections of MTC strains (n = 175 in total). Results: The utility of various polymorphisms as species-, lineage-, and sublineage-defining phylogenetic markers for M. africanum was determined. Novel SNPs were also identified and found to be specific to either M. africanum West African-1 (Rv1332 523; n = 32) or M. africanum West African-2 (nat 751; n = 27). In the final analysis, a strain identification approach that combined multi-primer PCR targeting of the RD loci RD9, RD10, and RD702 was the most simple, straight-forward, and definitive means of distinguishing the two clades of M. africanum from one another and from other MTC species. Conclusion: With this study, we have organized a series of consistent phylogenetically-relevant markers for each of the distinct MTC lineages that share the M. africanum designation. A differential distribution of each M. africanum clade in Western Africa is described

Phylogeny of Mycobacterium tuberculosis Beijing Strains Constructed from Polymorphisms in Genes Involved in DNA Replication, Recombination and Repair

The original publication is available at http:/www.plosone.orgBackground: The Beijing family is a successful group of M. tuberculosis strains, often associated with drug resistance and widely distributed throughout the world. Polymorphic genetic markers have been used to type particular M. tuberculosis strains. We recently identified a group of polymorphic DNA repair replication and recombination (3R) genes. It was shown that evolution of M. tuberculosis complex strains can be studied using 3R SNPs and a high-resolution tool for strain discrimination was developed. Here we investigated the genetic diversity and propose a phylogeny for Beijing strains by analyzing polymorphisms in 3R genes. Methodology/Principal Findings: A group of 3R genes was sequenced in a collection of Beijing strains from different geographic origins. Sequence analysis and comparison with the ones of non-Beijing strains identified several SNPs. These SNPs were used to type a larger collection of Beijing strains and allowed identification of 26 different sequence types for which a phylogeny was constructed. Phylogenetic relationships established by sequence types were in agreement with evolutionary pathways suggested by other genetic markers, such as Large Sequence Polymorphisms (LSPs). A recent Beijing genotype (Bmyc10), which included 60% of strains from distinct parts of the world, appeared to be predominant. Conclusions/Significance: We found SNPs in 3R genes associated with the Beijing family, which enabled discrimination of different groups and the proposal of a phylogeny. The Beijing family can be divided into different groups characterized by particular genetic polymorphisms that may reflect pathogenic features. These SNPs are new, potential genetic markers that may contribute to better understand the success of the Beijing family. © 2011 Mestre et al.Publishers' Versio

The sixth data release of the Radial Velocity Experiment (RAVE). I. Survey description, spectra and radial velocities

The Radial Velocity Experiment (RAVE) is a magnitude-limited (9<I<12) spectroscopic survey of Galactic stars randomly selected in the southern hemisphere. The RAVE medium-resolution spectra (R~7500) cover the Ca-triplet region (8410-8795A). The 6th and final data release (DR6 or FDR) is based on 518387 observations of 451783 unique stars. RAVE observations were taken between 12 April 2003 and 4 April 2013. Here we present the genesis, setup and data reduction of RAVE as well as wavelength-calibrated and flux-normalized spectra and error spectra for all observations in RAVE DR6. Furthermore, we present derived spectral classification and radial velocities for the RAVE targets, complemented by cross matches with Gaia DR2 and other relevant catalogs. A comparison between internal error estimates, variances derived from stars with more than one observing epoch and a comparison with radial velocities of Gaia DR2 reveals consistently that 68% of the objects have a velocity accuracy better than 1.4 km/s, while 95% of the objects have radial velocities better than 4.0 km/s. Stellar atmospheric parameters, abundances and distances are presented in subsequent publication. The data can be accessed via the RAVE Web (http://rave-survey.org) or the Vizier database.Comment: 32 pages, 11 figures, accepted for publication to A

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19

Investigation on Mycobacterium tuberculosis Diversity in China and the Origin of the Beijing Clade

Contains fulltext : 124314.pdf (publisher's version ) (Open Access