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      Nonlethal age estimation of three threatened fish species using DNA methylation: Australian lungfish, Murray cod and Mary River cod

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          Abstract

          Age‐based demography is fundamental to management of wild fish populations. Age estimates for individuals can determine rates of change in key life‐history parameters such as length, maturity, mortality and fecundity. These age‐based characteristics are critical for population viability analysis in endangered species and for developing sustainable harvest strategies. For teleost fish, age has traditionally been determined by counting increments formed in calcified structures such as otoliths. However, the collection of otoliths is lethal and therefore undesirable for threatened species. At a molecular level, age can be predicted by measuring DNA methylation. Here, we use previously identified age‐associated sites of DNA methylation in zebrafish ( Danio rerio) to develop two epigenetic clocks for three threatened freshwater fish species. One epigenetic clock was developed for the Australian lungfish ( Neoceratodus forsteri) and the second for the Murray cod ( Maccullochella peelii) and Mary River cod ( Maccullochella mariensis). Age estimation models were calibrated using either known‐age individuals, ages derived from otoliths or bomb radiocarbon dating of scales. We demonstrate a high Pearson's correlation between the chronological and predicted age in both the Lungfish clock (cor = .98) and Maccullochella clock (cor = .92). The median absolute error rate for both epigenetic clocks was also low (Lungfish = 0.86 years; Maccullochella = 0.34 years). This study demonstrates the transferability of DNA methylation sites for age prediction between highly phylogenetically divergent fish species. Given the method is nonlethal and suited to automation, age prediction by DNA methylation has the potential to improve fisheries and other wildlife management settings.

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          HISAT: a fast spliced aligner with low memory requirements.

          HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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            Regularization Paths for Generalized Linear Models via Coordinate Descent

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              DNA methylation age of human tissues and cell types

              Background It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure. Results I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance. Conclusions I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.
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                Author and article information

                Contributors
                benjamin.mayne@csiro.au
                Journal
                Mol Ecol Resour
                Mol Ecol Resour
                10.1111/(ISSN)1755-0998
                MEN
                Molecular Ecology Resources
                John Wiley and Sons Inc. (Hoboken )
                1755-098X
                1755-0998
                23 June 2021
                October 2021
                : 21
                : 7 ( doiID: 10.1111/men.v21.7 )
                : 2324-2332
                Affiliations
                [ 1 ] Environomics Future Science Platform Commonwealth Scientific and Industrial Research Organisation (CSIRO) Indian Ocean Marine Research Centre Crawley WA Australia
                [ 2 ] Department of Natural Resources, Mines and Energy Bundaberg Qld Australia
                [ 3 ] Seqwater Ipswich Qld Australia
                [ 4 ] Department of Primary Industries Grafton Fisheries Centre Grafton NSW Australia
                [ 5 ] Department of Agriculture, Fisheries and Forestry Brisbane Qld Australia
                [ 6 ] Australian Institute for Bioengineering and Nanotechnology The University of Queensland Brisbane Qld Australia
                [ 7 ] School of Biological Sciences The University of Western Australia, Crawley WA Australia
                Author notes
                [*] [* ] Correspondence

                Benjamin Mayne, Environomics Future Science Platform, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Indian Ocean Marine Research Centre, Crawley, WA, Australia.

                Email: benjamin.mayne@ 123456csiro.au

                Author information
                https://orcid.org/0000-0002-6750-8832
                Article
                MEN13440
                10.1111/1755-0998.13440
                8518777
                34161658
                1ede2140-4908-4b3b-8051-80621a00201d
                © 2021 The Authors. Molecular Ecology Resources published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 16 May 2021
                : 22 March 2021
                : 01 June 2021
                Page count
                Figures: 2, Tables: 2, Pages: 0, Words: 6801
                Funding
                Funded by: CSIRO , doi 10.13039/501100000943;
                Categories
                Resource Article
                RESOURCE ARTICLES
                Molecular and Statistical Advance
                Custom metadata
                2.0
                October 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.8 mode:remove_FC converted:15.10.2021

                Ecology
                age estimation,dna methylation,epigenetic clock,fish,wildlife management
                Ecology
                age estimation, dna methylation, epigenetic clock, fish, wildlife management

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