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      Systematic analyses with genomic and metabolomic insights reveal a new species, Ophiocordyceps indica sp. nov. from treeline area of Indian Western Himalayan region

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          Abstract

          Ophiocordyceps is a species-rich genus in the order Hypocreales ( Sordariomycetes, Ascomycota) depicting a fascinating relationship between microbes and insects. In the present study, a new species, Ophiocordyceps indica sp. nov., is discovered infecting lepidopteran larvae from tree line locations (2,202–2,653 m AMSL) of the Kullu District, Himachal Pradesh, Indian Western Himalayan region, using combinations of morphological and molecular phylogenetic analyses. A phylogeny for Ophiocordyceps based on a combined multigene (nr SSU, nr LSU, tef-1α, and RPB1) dataset is provided, and its taxonomic status within Ophiocordycipitaceae is briefly discussed. Its genome size (~59 Mb) revealed 94% genetic similarity with O. sinensis; however, it differs from other extant Ophiocordyceps species based on morphological characteristics, molecular phylogenetic relationships, and genetic distance. O. indica is identified as the second homothallic species in the family Ophiocordycipitaceae, after O. sinensis. The presence of targeted marker components, viz. nucleosides (2,303.25 μg/g), amino acids (6.15%), mannitol (10.13%), and biological activity data, suggests it to be a new potential source of nutraceutical importance. Data generated around this economically important species will expand our understanding regarding the diversity of Ophiocordyceps-like taxa from new locations, thus providing new research avenues.

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          RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

          Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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            BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs.

            Genomics has revolutionized biological research, but quality assessment of the resulting assembled sequences is complicated and remains mostly limited to technical measures like N50.
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              MEGA11: Molecular Evolutionary Genetics Analysis Version 11

              The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                20 July 2023
                2023
                : 14
                : 1188649
                Affiliations
                [1] 1Entomology Laboratory, Agrotechnology Division, CSIR-Institute of Himalayan Bioresource Technology (IHBT) , Palampur, HP, India
                [2] 2Academy of Scientific and Innovative Research (AcSIR) , Ghaziabad, India
                [3] 3Functional Genomics and Complex System Lab, Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology (IHBT) , Palampur, HP, India
                [4] 4Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology (IHBT) , Palampur, HP, India
                [5] 5Chemical Technology Division, CSIR-Institute of Himalayan Bioresource Technology (IHBT) , Palampur, HP, India
                Author notes

                Edited by: Rajesh Jeewon, University of Mauritius, Mauritius

                Reviewed by: Stefania Mirela Mang, University of Basilicata, Italy; Samantha Chandranath Karunarathna, Qujing Normal University, China; Jing Si, Beijing Forestry University, China

                *Correspondence: Vishal Acharya vishal@ 123456ihbt.res.in

                †These authors have contributed equally to this work

                Article
                10.3389/fmicb.2023.1188649
                10399244
                295b5b46-06c0-4a9e-aa86-92a657dd194d
                Copyright © 2023 Sharma, Kaur, Joshi, Kumari, Khatri, Swarnkar, Kumar, Acharya and Nadda.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 17 March 2023
                : 19 June 2023
                Page count
                Figures: 5, Tables: 8, Equations: 1, References: 106, Pages: 23, Words: 15453
                Funding
                Funded by: Indian Council of Medical Research, doi 10.13039/501100001411;
                Funded by: Council of Scientific and Industrial Research, India, doi 10.13039/501100001412;
                Funded by: Department of Biotechnology, Ministry of Science and Technology, India, doi 10.13039/501100001407;
                This study was supported by CSIR-India (PROMOTE BSC 0213; CeHAB BSC 0209; MLP-201, 202), Department of Biotechnology, Government of India, Bioinformatics facilities under the aegis of the Himalayan Center for High-throughput Computational Biology (HiCHiCoB; GAP-0282), and Senior Research Fellowships of Indian Council of Medical Research (ICMR).
                Categories
                Microbiology
                Original Research
                Custom metadata
                Evolutionary and Genomic Microbiology

                Microbiology & Virology
                genome,marker components,multigene phylogeny,new taxa,novel species,taxonomy
                Microbiology & Virology
                genome, marker components, multigene phylogeny, new taxa, novel species, taxonomy

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