TreeToReads - a pipeline for simulating raw reads from phylogenies.

BackgroundUsing phylogenomic analysis tools for tracking pathogens has become standard practice in academia, public health agencies, and large industries. Using the same raw read genomic data as input, there are several different approaches being used to infer phylogenetic tree. These include many different SNP pipelines, wgMLST approaches, k-mer algorithms, whole genome alignment and others; each of these has advantages and disadvantages, some have been extensively validated, some are faster, some have higher resolution. A few of these analysis approaches are well-integrated into the regulatory process of US Federal agencies (e.g. the FDA's SNP pipeline for tracking foodborne pathogens). However, despite extensive validation on benchmark datasets and comparison with other pipelines, we lack methods for fully exploring the effects of multiple parameter values in each pipeline that can potentially have an effect on whether the correct phylogenetic tree is recovered.ResultsTo resolve this problem, we offer a program, TreeToReads, which can generate raw read data from mutated genomes simulated under a known phylogeny. This simulation pipeline allows direct comparisons of simulated and observed data in a controlled environment. At each step of these simulations, researchers can vary parameters of interest (e.g., input tree topology, amount of sequence divergence, rate of indels, read coverage, distance of reference genome, etc) to assess the effects of various parameter values on correctly calling SNPs and reconstructing an accurate tree.ConclusionsSuch critical assessments of the accuracy and robustness of analytical pipelines are essential to progress in both research and applied settings

A Policy Brief: Massachusetts (T)AFDC Case Closings, October 1993-August 1997

When a DTA (Department of Transitional Assistance) worker assesses whether a family\u27s (T)AFDC (Temporary Aid to Families with Dependent Children) case will be closed, s/he decides which one of 67 different codes best describes the reason cash benefits for the household will be stopped. To carry out the analyses, we sorted all of the 67 codes into clusters of codes that logically grouped together: Cluster I, Increased Income; Cluster H, Sanctions; Cluster III, Eligible Persons Moved; Cluster IV, Fraud; Cluster V, Client Request; Cluster VI, No Longer Eligible; Cluster VII, Other or Multiple Meanings. The Appendix displays a description of the case closing codes in each cluster that provided a basis for our analyses. We used SPSS (Statistical Package for the Social Sciences) to calculate the trends in the number and percentages of case closings from October, 1995 to August, 1997 for each of the clusters mentioned above, and from October, 1993 to August, 1997 for the category of Earned Income only (a sub-set of Cluster I, Increased Income). We used four time periods for our analysis of earned income case closings, reflecting the progression of events surrounding the passage and full implementation of Massachusetts\u27 welfare reform measures. These time periods are: October 1993 to September 1994, former AFDC phase; October 1994 to September 1995, legislative deliberation and passage phase; October 1995 to September 1996, initial implementation phase; and October 1996 to August 1997, the most recent implementation phase

Evolution of Massive Stars at Low Metallicity

This paper reports the contributions made on the occasion of the Special Session entitled "Evolution of Massive Stars at Low Metallicity” which was held on Sunday, December 9, 2007 in Kauai (USA

Physical Properties of Young Brown Dwarfs and Very Low-Mass Stars Inferred from High-Resolution Model Spectra

By comparing near-infrared spectra with atmosphere models, we infer the effective temperature, surface gravity, projected rotational velocity, and radial velocity for 21 very-low-mass stars and brown dwarfs. The unique sample consists of two sequences in spectral type from M6-M9, one of 5-10 Myr objects and one of >1 Gyr field objects. A third sequence is comprised of only ~M6 objects with ages ranging from 1 Gyr. Spectra were obtained in the J band at medium (R~2,000) and high (R~20,000) resolutions with NIRSPEC on the Keck II telescope. Synthetic spectra were generated from atmospheric structures calculated with the PHOENIX model atmosphere code. Using multi-dimensional least-squares fitting and Monte Carlo routines we determine the best-fit model parameters for each observed spectrum and note which spectral regions provide consistent results. We identify successes in the reproduction of observed features by atmospheric models, including pressure-broadened KI lines, and investigate deficiencies in the models, particularly missing FeH opacity, that will need to be addressed in order to extend our analysis to cooler objects. The precision that can be obtained for each parameter using medium- and high- resolution near-infrared spectra is estimated and the implications for future studies of very low mass stars and brown dwarfs are discussed.Comment: Accepted to the Astrophysical Journal Supplement Serie

Cytochrome c4 is required for siderophore expression by Legionella pneumophila, whereas cytochromes c1 and c5 promote intracellular infection

A panel of cytochrome c maturation (ccm) mutants of Legionella pneumophila displayed a loss of siderophore (legiobactin) expression, as measured by both the chrome azurol S assay and a Legionella-specific bioassay. These data, coupled with the finding that ccm transcripts are expressed by wild-type bacteria grown in deferrated medium, indicate that the Ccm system promotes siderophore expression by L. pneumophila. To determine the basis of this newfound role for Ccm, we constructed and tested a set of mutants specifically lacking individual c-type cytochromes. Whereas ubiquinol-cytochrome c reductase (petC) mutants specifically lacking cytochrome c1 and cycB mutants lacking cytochrome c5 had normal siderophore expression, cyc4 mutants defective for cytochrome c4 completely lacked legiobactin. These data, along with the expression pattern of cyc4 mRNA, indicate that cytochrome c4 in particular promotes siderophore expression. In intracellular infection assays, petC mutants and cycB mutants, but not cyc4 mutants, had a reduced ability to infect both amoebae and macrophage hosts. Like ccm mutants, the cycB mutants were completely unable to grow in amoebae, highlighting a major role for cytochrome c5 in intracellular infection. To our knowledge, these data represent both the first direct documentation of the importance of a c-type cytochrome in expression of a biologically active siderophore and the first insight into the relative importance of c-type cytochromes in intracellular infection events

Digitization workflows for flat sheets and packets of plants, algae, and fungi

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141708/1/aps31500065.pd

Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 x 10(-8)) with GDM, mapping to/near MTNR1B (P = 4.3 x 10(-54)), TCF7L2 (P = 4.0 x 10(-16)), CDKAL1 (P = 1.6 x 10(-4)), CDKN2A-CDKN2B (P = 4.1 x 10(-9)) and HKDC1 (P = 2.9 x 10(-8)). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.Peer reviewe

Meta-analysis of epigenome-wide association studies in newborns and children show widespread sex differences in blood DNA methylation

Publisher Copyright: © 2022 The AuthorsBackground: Among children, sex-specific differences in disease prevalence, age of onset, and susceptibility have been observed in health conditions including asthma, immune response, metabolic health, some pediatric and adult cancers, and psychiatric disorders. Epigenetic modifications such as DNA methylation may play a role in the sexual differences observed in diseases and other physiological traits. Methods: We performed a meta-analysis of the association of sex and cord blood DNA methylation at over 450,000 CpG sites in 8438 newborns from 17 cohorts participating in the Pregnancy And Childhood Epigenetics (PACE) Consortium. We also examined associations of child sex with DNA methylation in older children ages 5.5–10 years from 8 cohorts (n = 4268). Results: In newborn blood, sex was associated at Bonferroni level significance with differences in DNA methylation at 46,979 autosomal CpG sites (p < 1.3 × 10−7) after adjusting for white blood cell proportions and batch. Most of those sites had lower methylation levels in males than in females. Of the differentially methylated CpG sites identified in newborn blood, 68% (31,727) met look-up level significance (p < 1.1 × 10−6) in older children and had methylation differences in the same direction. Conclusions: This is a large-scale meta-analysis examining sex differences in DNA methylation in newborns and older children. Expanding upon previous studies, we replicated previous findings and identified additional autosomal sites with sex-specific differences in DNA methylation. Differentially methylated sites were enriched in genes involved in cancer, psychiatric disorders, and cardiovascular phenotypes.Peer reviewe