Fitting Percentage of Body Fat to Simple Body Measurements: College Women

Percentage of body fat, age, weight, height, and 14 circumference measurements (e.g., waist) are given for 184 women aged 18–25. Body fat, one measure of health, was accurately determined by an underwater weighing technique which requires special equipment and training of the individuals conducting the process. Modeling body fat percentage using multiple regression provides a convenient method of estimating body fat percentage using measures collected using only a measuring tape and a scale. This dataset can be used to show students the utility of multiple regression and to provide practice in model building.

Online Phylogenetics with matOptimize Produces Equivalent Trees and is Dramatically More Efficient for Large SARS-CoV-2 Phylogenies than de novo and Maximum-Likelihood Implementations.

Phylogenetics has been foundational to SARS-CoV-2 research and public health policy, assisting in genomic surveillance, contact tracing, and assessing emergence and spread of new variants. However, phylogenetic analyses of SARS-CoV-2 have often relied on tools designed for de novo phylogenetic inference, in which all data are collected before any analysis is performed and the phylogeny is inferred once from scratch. SARS-CoV-2 datasets do not fit this mold. There are currently over 14 million sequenced SARS-CoV-2 genomes in online databases, with tens of thousands of new genomes added every day. Continuous data collection, combined with the public health relevance of SARS-CoV-2, invites an "online" approach to phylogenetics, in which new samples are added to existing phylogenetic trees every day. The extremely dense sampling of SARS-CoV-2 genomes also invites a comparison between likelihood and parsimony approaches to phylogenetic inference. Maximum likelihood (ML) and pseudo-ML methods may be more accurate when there are multiple changes at a single site on a single branch, but this accuracy comes at a large computational cost, and the dense sampling of SARS-CoV-2 genomes means that these instances will be extremely rare because each internal branch is expected to be extremely short. Therefore, it may be that approaches based on maximum parsimony (MP) are sufficiently accurate for reconstructing phylogenies of SARS-CoV-2, and their simplicity means that they can be applied to much larger datasets. Here, we evaluate the performance of de novo and online phylogenetic approaches, as well as ML, pseudo-ML, and MP frameworks for inferring large and dense SARS-CoV-2 phylogenies. Overall, we find that online phylogenetics produces similar phylogenetic trees to de novo analyses for SARS-CoV-2, and that MP optimization with UShER and matOptimize produces equivalent SARS-CoV-2 phylogenies to some of the most popular ML and pseudo-ML inference tools. MP optimization with UShER and matOptimize is thousands of times faster than presently available implementations of ML and online phylogenetics is faster than de novo inference. Our results therefore suggest that parsimony-based methods like UShER and matOptimize represent an accurate and more practical alternative to established maximum likelihood implementations for large SARS-CoV-2 phylogenies and could be successfully applied to other similar datasets with particularly dense sampling and short branch lengths.

Analysis of Mutational Profiles of SARS-CoV-2 Structural and Non-Structural Proteins with Emphasis on Spike Protein Variants

SARS-CoV-2 has very recently posed a potential threat to humanity due to its very rapid rate of mutations and repairing mechanism. The spread of this virus is considered to have occurred in Wuhan, China in December 2019. Characterized by high rates of transmission, the virus is constantly evolving towards attaining higher rates of stability and transmissibility through acquiring mutations in its genome. Therefore, this study aims to analyse the mutational profiles of SARS-CoV-2 isolates. Analysis of the mutational profiles in individual SARS-CoV-2 proteins will allow us to look into the rates of mutations associated with each protein. Frequently mutated residues have been identified in this research by aligning 688 SARS-CoV-2 nucleotide sequences, which were downloaded from NCBI (National Center For Biotechnology Information) repository. Further, mutational frequencies of these mutated residues have been studied, which is instrumental in identifying the proteins that are resistant to changes, as well as the ones that have a greater proclivity towards incorporating mutations. © 2022, Walailak University. All rights reserved.

Ongoing Recombination in SARS-CoV-2 Revealed through Genealogical Reconstruction.

The evolutionary process of genetic recombination has the potential to rapidly change the properties of a viral pathogen, and its presence is a crucial factor to consider in the development of treatments and vaccines. It can also significantly affect the results of phylogenetic analyses and the inference of evolutionary rates. The detection of recombination from samples of sequencing data is a very challenging problem and is further complicated for SARS-CoV-2 by its relatively slow accumulation of genetic diversity. The extent to which recombination is ongoing for SARS-CoV-2 is not yet resolved. To address this, we use a parsimony-based method to reconstruct possible genealogical histories for samples of SARS-CoV-2 sequences, which enables us to pinpoint specific recombination events that could have generated the data. We propose a statistical framework for disentangling the effects of recurrent mutation from recombination in the history of a sample, and hence provide a way of estimating the probability that ongoing recombination is present. We apply this to samples of sequencing data collected in England and South Africa and find evidence of ongoing recombination.

A parsimonious approach for recognizing SARS-CoV-2 and host interactions.

Effective countermeasures against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demand a better understanding of the pathogen-host interactions. However, such information about the targets, responses, and effects in the host due to the virus is limited, especially so in the case of newly emerged pathogens. The peptide domains that form the interfaces of host and pathogen interacting proteins being evolutionarily conserved, it may be hypothesized that such interactions can be inferred from the similarities in the nucleotide sequences between the host and the pathogen. This communication reports the results of a study based on a parsimonious approach for the identification of the host-virus interactions, where sequence complementarity between the human and SARS-Cov-2 genomes was used to predict several interactions between the host and SARS-CoV-2 at different levels of biological organization. In particular, the findings are suggestive of a direct effect of SARS-CoV-2 on cardiac health. The existing literature on host responses to SARS-CoV-2 and other viruses attest to many of these predicted interactions, supporting the utility of the proposed approach for the identification of host interactions with other novel pathogens.

The phylogenetic relationship within SARS-CoV-2s: An expanding basal clade.

The COVID-19 pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) whose origin is still shed in mystery. In this study, we developed a method to search the basal SARS-CoV-2 clade among collected SARS-CoV-2 genome sequences. We first identified the mutation sites in the SARS-CoV-2 whole genome sequence alignment. Then by the pairwise comparison of the numbers of mutation sites among all SARS-CoV-2s, the least mutated clade was identified, which is the basal clade under parsimony principle. In our first analysis, we used 168 SARS-CoV-2 sequences (GISAID dataset till 2020/03/04) to identify the basal clade which contains 33 identical viral sequences from seven countries. To our surprise, in our second analysis with 367 SARS-CoV-2 sequences (GISAID dataset till 2020/03/17), the basal clade has 51 viral sequences, 18 more sequences added. The much larger NCBI dataset shows that this clade has expanded with 85 unique sequences by 2020/04/04. The expanding basal clade tells a chilling fact that the least mutated SARS-CoV-2 sequence was replicating and spreading for at least four months. It is known that coronaviruses have the RNA proofreading capability to ensure their genome replication fidelity. Interestingly, we found that the SARS-CoV-2 without its nonstructural proteins 13 to 16 (Nsp13-Nsp16) exhibits an unusually high mutation rate. Our result suggests that SARS-CoV-2 has an unprecedented RNA proofreading capability which can intactly preserve its genome even after a long period of transmission. Our selection analyses also indicate that the positive selection event enabling SARS-CoV-2 to cross species and adapt to human hosts might have been achieved before its outbreak.

Genomic exploration light on multiple origin with potential parsimony-informative sites of the severe acute respiratory syndrome coronavirus 2 in Bangladesh.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new strain of beta coronavirus that has spread worldwide within a short period of time and has been responsible for the current COVID-19 pandemic. This novel virus shows high transmission and adaptability frequency into the host with rapid changes in genomic sequences. In this study, we analyzed the complete genome of 41 strains isolated in Bangladesh to understand the evolutionary route and genetic variations of this rapidly evolving virus. The phylogenetics, parsimony informative sites and mutation analyses were performed using MEGA X, Multiple sequence alignment program (MAFFT), and Virus Pathogen Resource. The phylogenetic analysis of the studied genomes along with the reference genome suggested that the viral strains found in Bangladesh might be coming from multiple countries such as France, Germany, India, the USA, and Brazil. After entering into the country, intra-cluster and inter-cluster began to circulate in the 8 individual divisions of Bangladesh. We also identified 26 parsimony-informative sites along with the 9 most important sites for virus evolution. Genome-wide annotations revealed 256 mutations, of which 10 were novel (NSP3, RdRp, Spike) in Bangladeshi strains where I120F(NSP2), P323L(RdRp), D614G (Spike), R203K, G204R(N) are the most prominent. Most importantly, numerous mutations were flourishing in the N protein gene (67) followed by S (45), RdRp (38), NSP2 (34), NSP3 (20), and ORF8 (6) gene. Moreover, nucleotide deletion analysis found nine deletions throughout the genomes including in ORF7a (8), ORF8 (1) with one insertion (G) at 265 positions in only one genome. The underlying mechanism of disease severity, molecular evolution, and epidemiology lie in genomic sequences that are not fully understood yet. Identification of the evolutionary history, parsimony-informative sites and others genetic variations of this deadly virus will facilitate the development of new strategies to control the local transmission and provide deep insight in the identification of potential therapeutic targets for controlling COVID-19.