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MATO: An updated tool for capturing and analyzing cytotaxonomic and morphological data

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  • Corresponding author: yyu@scu.edu.cn
    1. Current tools for morphology and cytotaxonomy measurements face challenges in providing consistent results and compatibility with statistical analysis.

      MATO (Measurement and Analysis Tools), an upgraded version of our previous KaryoType software, is introduced to address these shortcomings.

      MATO improves chromosome measurements and karyotype analysis through the incorporation of size-based Karyotyping and a novel grouping algorithm.

      This tool accommodates a wide variety of morphometric characters such as length, size, angle, count, and color, which are often employed in morphological studies.

  • Advancements in bioinformatics and genomics have heightened the significance of cytotaxonomy and morphology as fields of study. The quantification of various characters forms the basis of morphological investigations. However, due to variations among characters across different taxa, manual measurements are commonly employed. Yet, existing measurement tools for morphology and cytotaxonomy lack repeatability and statistical analysis compatibility. To address these limitations, we have developed MATO (Measurement and Analysis tools) as an updated version of the KaryoType software. MATO aims to accelerate repetitive morphometric tasks and yield quantitative and reproducible outcomes. By introducing size-based Karyotyping and a novel grouping algorithm, MATO enhances chromosome measurements and karyotype analysis. Additionally, MATO encompasses a broad range of morphometric characters, including length, size, angle, count, and color, frequently utilized in plant taxonomy. It features an improved graphic user interface for macOS and Windows operating systems and is available for free download at https://github.com/sculab/MATO. MATO empowers researchers in the fields of cytotaxonomy and morphology by providing enhanced measurement capabilities, statistical analysis compatibility, and improved user-friendliness, facilitating advancements in their research endeavors.
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  • [1] Buzgo, M., Soltis, D.E., Soltis, P.S., et al. (2004). Towards a comprehensive integration of morphological and genetic studies of floral development. Trends Plant Sci. 9 : 164-173, 10.1016/j.tplants.2004.02.003.

    View in Article Google Scholar

    [2] Wortley, A.H. and Scotland, R.W. (2006). The effect of combining molecular and morphological data in published phylogenetic analyses. Syst. Biol. 55: 677−685. DOI: 10.1080/10635150600899798.

    View in Article CrossRef Google Scholar

    [3] Faraut, T. (2008). Addressing chromosome evolution in the whole-genome sequence era. Chromosome Research 16: 5−16. DOI: 10.1007/s10577-007-1208-0.

    View in Article CrossRef Google Scholar

    [4] Gokhman, V.E. (2022). Comparative karyotype analysis of parasitoid hymenoptera (insecta): Major approaches, techniques, and results. Genes (Basel) 13: 751. DOI: 10.3390/genes13050751.

    View in Article CrossRef Google Scholar

    [5] Endress, P.K., Baas, P., and Gregory, M. (2000). Systematic plant morphology and anatomy - 50 years of progress. Taxon 49: 401−434. DOI: 10.2307/1224342.

    View in Article CrossRef Google Scholar

    [6] Henderson, A. (2006). Traditional morphometrics in plant systematics and its role in palm systematics. Bot. J. Linn. Soc. 15: 103−111. DOI: 10.1111/j.1095-8339.2006.00526.x.

    View in Article CrossRef Google Scholar

    [7] Vimala, Y., Lavania, S., and Lavania, U.C. (2021). Chromosome change and karyotype differentiation–implications in speciation and plant systematics. The Nucleus 64: 33−54. DOI: 10.1007/s13237-020-00343-y.

    View in Article CrossRef Google Scholar

    [8] Qiang, W., Zi-Hui, T., Zi-Wei, L., et al. (2019). Karyotypes of seven Chinese species of Fritillaria ( Liliaceae). Plant Sci. J. 37: 434−440. DOI: 10.11913/PSJ.2095-0837.2019.40434.

    View in Article CrossRef Google Scholar

    [9] Singh, H., Kumar, P., and Singh, S.K. (2022). Cytological studies in endangered phlomoides superba (Royle ex Benth. ) Kamelin & Makhm. Cytologia 87: 195−200. DOI: 10.1508/cytologia.87.195.

    View in Article CrossRef Google Scholar

    [10] Friesen, N., Grutzmacher, L., Skaptsov, M., et al. (2022). Allium pallasii and A. caricifolium-surprisingly diverse old steppe species, showing a clear geographical barrier in the area of lake Zaysan. Plants-Basel 11: 1465. DOI: 10.3390/plants11111465.

    View in Article CrossRef Google Scholar

    [11] Giaco, A., De Giorgi, P., Astuti, G., et al. (2022). Diploids and polyploids in the Santolina chamaecyparissus complex (Asteraceae) show different karyotype asymmetry. Plant Biosyst. 156: 1237−1246. DOI: 10.1080/11263504.2022.2029971.

    View in Article CrossRef Google Scholar

    [12] Rueden, C.T., Schindelin, J., Hiner, M.C., et al. (2017). ImageJ2: ImageJ for the next generation of scientific image data. BMC Bioinf. 18: 529. DOI: 10.1186/s12859-017-1934-z.

    View in Article CrossRef Google Scholar

    [13] Schindelin, J., Rueden, C.T., Hiner, M.C., et al. (2015). The ImageJ ecosystem: An open platform for biomedical image analysis. Mol. Reprod. Dev. 82: 518−529. DOI: 10.1002/mrd.22489.

    View in Article CrossRef Google Scholar

    [14] Schroeder, A.B., Dobson, E.T.A., Rueden, C.T., et al. (2021). The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis. Protein Sci. 30: 234−249. DOI: 10.1002/pro.3993.

    View in Article CrossRef Google Scholar

    [15] Kankaanpaa, P., Paavolainen, L., Tiitta, S., et al. (2012). BioImageXD: An open, general-purpose and high-throughput image-processing platform. Nat. Methods 9: 683−689. DOI: 10.1038/nmeth.2047.

    View in Article CrossRef Google Scholar

    [16] Kirov, I., Khrustaleva, L., Laere, K.V., et al. (2017). DRAWID: User-friendly java software for chromosome measurements and idiogram drawing. Comp. Cytogenet. 11: 747−757. DOI: 10.3897/CompCytogen.v11i4.20830.

    View in Article CrossRef Google Scholar

    [17] Mirzaghaderi, G. and Marzangi, K. (2015). IdeoKar: An ideogram constructing and karyotype analyzing software. Caryologia 68: 31−35. DOI: 10.1080/00087114.2014.998526.

    View in Article CrossRef Google Scholar

    [18] Altınordu, F., Peruzzi, L., Yu, Y., et al. (2016). A tool for the analysis of chromosomes: KaryoType. Taxon 65: 586−592. DOI: 10.12705/653.9.

    View in Article CrossRef Google Scholar

    [19] Liao, C.Y., Gao, Q., Katz-Downie, D.S., et al. (2022). A systematic study of North American Angelica species (Apiaceae) based on nrDNA ITS and cpDNA sequences and fruit morphology. J. Syst. Evol. 60: 789−808. DOI: 10.1111/jse.12702.

    View in Article CrossRef Google Scholar

    [20] Zhou, Y.Y., Si, Y.H., Zhang, Z., et al. (2021). Codonopsis atriplicifolia (Campanulaceae), a new species from western Sichuan, China. Phytotaxa 512: 197−204. DOI: 10.11646/phytotaxa.512.3.7.

    View in Article CrossRef Google Scholar

    [21] Xie, D.-F., Xie, F.-M., Jia, S.-B., et al. (2020). Allium xinlongense (Amaryllidaceae, Allioideae), a new species from western Sichuan. Phytotaxa 432: 274−282. DOI: 10.11646/phytotaxa.432.3.4.

    View in Article CrossRef Google Scholar

    [22] Astuti, G., Roma-Marzio, F., and Peruzzi, L. (2015). The genus Picris (Asteraceae) in southern Italy: Contribution to its systematic knowledge. Phytotaxa 207: 106−114. DOI: 10.11646/phytotaxa.207.1.5.

    View in Article CrossRef Google Scholar

    [23] Moore, L.S., Wei, W., Stolovicki, E., et al. (2014). Induced mutations in yeast cell populations adapting to an unforeseen challenge. PLoS One 9: e111133. DOI: 10.1371/journal.pone.0111133.

    View in Article CrossRef Google Scholar

    [24] Panzer, S., Piombino-Mascali, D., and Zink, A.R. (2012). Herniation pits in human mummies: A CT investigation in the Capuchin Catacombs of Palermo, Sicily. PLoS One 7: e36537. DOI: 10.1371/journal.pone.0036537.

    View in Article CrossRef Google Scholar

    [25] Hermawan, H.O. (2021). The underlying data of transdifferentiation of human peripheral blood CD34+ cells into mature cardiomyocyte-like cells using micro RNA-1 research. Figshare.

    View in Article Google Scholar

    [26] Li, J., Zhou, S.-D., Yang, M.E.I., et al. (2020). Notholirion campanulatum is co-specific with N. bulbuliferum (Liliaceae) based on morphology and molecular data. Phytotaxa 471: 234−246. DOI: 10.11646/phytotaxa.471.3.5.

    View in Article CrossRef Google Scholar

    [27] Qin, G., Zong, Y., Chen, Q., et al. (2010). Inhibitory effect of boron against Botrytis cinerea on table grapes and its possible mechanisms of action. Int. J. Food Microbiol. 138: 145−150. DOI: 10.1016/j.ijfoodmicro.2009.12.018.

    View in Article CrossRef Google Scholar

    [28] Wang, J., Xia, X.M., Wang, H.Y., et al. (2013). Inhibitory effect of lactoferrin against gray mould on tomato plants caused by Botrytis cinerea and possible mechanisms of action. Int. J. Food Microbiol. 161: 151−157. DOI: 10.1016/j.ijfoodmicro.2012.11.025.

    View in Article CrossRef Google Scholar

    [29] Levan, A., Fredga, K., and Sandberg, A.A. (1964). Nomenclature for Centromeric Position on Chromosomes. Hereditas 52: 201−220. DOI: 10.1111/j.1601-5223.1964.tb01953.x.

    View in Article CrossRef Google Scholar

    [30] Stebbins, G.L. (1971). Chromosomal evolution in higher plants. Q. Rev. Biol. 48: 30.

    View in Article Google Scholar

    [31] Peruzzi, L. and Eroglu, H.E. (2013). Karyotype asymmetry: Again, how to measure and what to measure. Comp. Cytogenet. 7: 1−9. DOI: 10.3897/CompCytogen.v7i1.4431.

    View in Article CrossRef Google Scholar

    [32] Paszko, B. (2006). A critical review and a new proposal of karyotype asymmetry indices. Plant Syst. Evol. 258: 39−48. DOI: 10.1007/s00606-005-0389-2.

    View in Article CrossRef Google Scholar

    [33] Astuti, G., Roma-Marzio, F., and Peruzzi, L. (2016). Traditional cytotaxonomic studies: Can they still provide a solid basis in plant systematics? XV OPTIMA Meeting DOI: 10.13140/RG.2.1.4959.3845.

    View in Article Google Scholar

    [34] Kaplan, D.R. (2001). The science of plant morphology: Definition, history, and role in modern biology. Am. J. Bot. 88: 1711−1741. DOI: 10.2307/3558347.

    View in Article CrossRef Google Scholar

    [35] Bentzer, B., Bothmer, R.v., Engstrand, L., et al. (1971). Some sources of error in the determination of arm ratios of chromosomes. Bot. Notiser 124: 65−74.

    View in Article Google Scholar

    [36] Hsu, P., Zhang, Z., Chen, J., and Hong, D. (1996). Advances in chromosome studies and plant taxonomy. J. Wuhan Bot. Res. 14: 261−268.

    View in Article Google Scholar

  • Cite this article:

    Liu L., Wang Q., Zhang Z., et al., (2023). MATO: An updated tool for capturing and analyzing cytotaxonomic and morphological data. The Innovation Life 1(1), 100010. https://doi.org/10.59717/j.xinn-life.2023.100010
    Liu L., Wang Q., Zhang Z., et al., (2023). MATO: An updated tool for capturing and analyzing cytotaxonomic and morphological data. The Innovation Life 1(1), 100010. https://doi.org/10.59717/j.xinn-life.2023.100010

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