start-ver=1.4 cd-journal=joma no-vol=90 cd-vols= no-issue=1 article-no= start-page=29 end-page=36 dt-received= dt-revised= dt-accepted= dt-pub-year=2025 dt-pub=20250325 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Elucidation of the phylogenetic relationships among <i>Alpinia</i> species native to the Nansei Islands, Japan en-subtitle= kn-subtitle= en-abstract= kn-abstract=The Alpinia species (A. intermedia, A. zerumbet, A. formosana, A. uraiensis, and unidentified strains native to the Daito Islands), which are native to the Nansei Islands, Japan are ornamental plants that can be used as resources to produce seasonings and antibacterial and antiviral substances. Despite the usefulness of these plants, little scientific research has been conducted on their phylogenetic relationships. In this study, their phylogenetic relationships were examined based on genomic and chloroplast DNA polymorphisms, repetitive sequence abundance, and cytogenetic perspectives. The results indicated that A. formosana is most likely the outcome of a hybrid of A. zerumbet and A. intermedia, and the unidentified strains native to the Daito Islands are the outcomes of a hybrid of A. zerumbet and A. uraiensis. Immunostaining with a newly produced anti-centromere-specific histone H3 (CENH3) antibody revealed that the number of chromosomes in these species was 2n=48. en-copyright= kn-copyright= en-aut-name=NagakiKiyotaka en-aut-sei=Nagaki en-aut-mei=Kiyotaka kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=NarusakaMari en-aut-sei=Narusaka en-aut-mei=Mari kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=NarusakaYoshihiro en-aut-sei=Narusaka en-aut-mei=Yoshihiro kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= affil-num=1 en-affil=Institute of Plant Science and Resources, Okayama University kn-affil= affil-num=2 en-affil=Okayama Prefectural Technology Center for Agriculture, Forestry, and Fisheries, Research Institute for Biological Sciences (RIBS) kn-affil= affil-num=3 en-affil=Okayama Prefectural Technology Center for Agriculture, Forestry, and Fisheries, Research Institute for Biological Sciences (RIBS) kn-affil= en-keyword=Alpinia kn-keyword=Alpinia en-keyword=Nansei Islands kn-keyword=Nansei Islands en-keyword=Chromosome number kn-keyword=Chromosome number en-keyword=CENH3 (centromere-specific histone H3) kn-keyword=CENH3 (centromere-specific histone H3) END start-ver=1.4 cd-journal=joma no-vol=7 cd-vols= no-issue=12 article-no= start-page=e202402802 end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2024 dt-pub=20241001 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Chromosome-specific barcode system with centromeric repeat in cultivated soybean and wild progenitor en-subtitle= kn-subtitle= en-abstract= kn-abstract=Wild soybean Glycine soja is the progenitor of cultivated soybean Glycine max. Information on soybean functional centromeres is limited despite extensive genome analysis. These species are an ideal model for studying centromere dynamics for domestication and breeding. We performed a detailed chromatin immunoprecipitation analysis using centromere-specific histone H3 protein to delineate two distinct centromeric DNA sequences with unusual repeating units with monomer sizes of 90–92 bp (CentGm-1) and 413-bp (CentGm-4) shorter and longer than standard nucleosomes. These two unrelated DNA sequences with no sequence similarity are part of functional centromeres in both species. Our results provide a comparison of centromere properties between a cultivated and a wild species under the effect of the same kinetochore protein. Possible sequence homogenization specific to each chromosome could highlight the mechanism for evolutionary conservation of centromeric properties independent of domestication and breeding. Moreover, a unique barcode system to track each chromosome is developed using CentGm-4 units. Our results with a unifying centromere composition model using CentGm-1 and CentGm-4 superfamilies could have far-reaching implications for comparative and evolutionary genome research. en-copyright= kn-copyright= en-aut-name=TekAhmet L en-aut-sei=Tek en-aut-mei=Ahmet L kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=NagakiKiyotaka en-aut-sei=Nagaki en-aut-mei=Kiyotaka kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=Yıldız AkkamışHümeyra en-aut-sei=Yıldız Akkamış en-aut-mei=Hümeyra kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=TanakaKeisuke en-aut-sei=Tanaka en-aut-mei=Keisuke kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=KobayashiHisato en-aut-sei=Kobayashi en-aut-mei=Hisato kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= affil-num=1 en-affil=Department of Agricultural Genetic Engineering, Ayhan Şahenk Faculty of Agricultural Sciences and Technologies, Niğde Ömer Halisdemir University kn-affil= affil-num=2 en-affil=Institute of Plant Science and Resources, Okayama University kn-affil= affil-num=3 en-affil=Department of Agricultural Genetic Engineering, Ayhan Şahenk Faculty of Agricultural Sciences and Technologies, Niğde Ömer Halisdemir University kn-affil= affil-num=4 en-affil=NODAI Genome Research Center, Tokyo University of Agriculture kn-affil= affil-num=5 en-affil=NODAI Genome Research Center, Tokyo University of Agriculture kn-affil= END start-ver=1.4 cd-journal=joma no-vol=37 cd-vols= no-issue=7 article-no= start-page=koaf142 end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2025 dt-pub=20250610 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Pancentromere analysis of Allium species reveals diverse centromere positions in onion and gigantic centromeres in garlic en-subtitle= kn-subtitle= en-abstract= kn-abstract=In eukaryotes, centromeres interact with the kinetochore for distribution of genetic information in cell division, yet their sequence and size are diverse among species. However, their position on chromosomes is considered to be conserved within a species. In this study, we analyzed the centromeres of 3 Allium species, namely, Welsh onion (Allium fistulosum), onion (Allium cepa), and garlic (Allium sativum) via pancentromere analysis and repetitive sequence analysis of centromeres and their neighborhoods and revealed their mobility, sequence organization, and size. Among the 3 species, Welsh onion and garlic had stable centromeres, but the onion centromere appeared to be polymorphic and frequently differed in position by up to 28.0 Mb among cultivars and between multiple individuals of the same cultivar. This mobility was stabilized by hybridization with Welsh onions. Furthermore, these 3 species have very different centromere sequence organization, including differences in the existence and maturity of centromeric satellites, and differences in centromere size, with Welsh onion having a centromere of 1.9 Mb, and garlic having a centromere of ∼10.6 Mb, the largest of any organism with monocentric chromosomes analyzed to date. Our pancentromere analysis of these Allium species reveals the variation in sequence organization, size, and position of this important chromosomal region. en-copyright= kn-copyright= en-aut-name=NagakiKiyotaka en-aut-sei=Nagaki en-aut-mei=Kiyotaka kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=UshijimaKoichiro en-aut-sei=Ushijima en-aut-mei=Koichiro kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=AkagiTakashi en-aut-sei=Akagi en-aut-mei=Takashi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=TanakaKeisuke en-aut-sei=Tanaka en-aut-mei=Keisuke kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=KobayashiHisato en-aut-sei=Kobayashi en-aut-mei=Hisato kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= affil-num=1 en-affil=Institute of Plant Science and Resources, Okayama University kn-affil= affil-num=2 en-affil=Graduate School of Environmental and Life Science, Okayama University kn-affil= affil-num=3 en-affil=Graduate School of Environmental and Life Science, Okayama University kn-affil= affil-num=4 en-affil=NODAI Genome Research Center, Tokyo University of Agriculture kn-affil= affil-num=5 en-affil=NODAI Genome Research Center, Tokyo University of Agriculture kn-affil= END start-ver=1.4 cd-journal=joma no-vol=637 cd-vols= no-issue=8046 article-no= start-page=744 end-page=748 dt-received= dt-revised= dt-accepted= dt-pub-year=2025 dt-pub=20250101 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Centrophilic retrotransposon integration via CENH3 chromatin in Arabidopsis en-subtitle= kn-subtitle= en-abstract= kn-abstract=In organisms ranging from vertebrates to plants, major components of centromeres are rapidly evolving repeat sequences, such as tandem repeats (TRs) and transposable elements (TEs), which harbour centromere-specific histone H3 (CENH3)1,2. Complete centromere structures recently determined in human and Arabidopsis suggest frequent integration and purging of retrotransposons within the TR regions of centromeres3,4,5. Despite the high impact of ‘centrophilic’ retrotransposons on the paradox of rapid centromere evolution, the mechanisms involved in centromere targeting remain poorly understood in any organism. Here we show that both Ty3 and Ty1 long terminal repeat retrotransposons rapidly turnover within the centromeric TRs of Arabidopsis species. We demonstrate that the Ty1/Copia element Tal1 (Transposon of Arabidopsis lyrata 1) integrates de novo into regions occupied by CENH3 in Arabidopsis thaliana, and that ectopic expansion of the CENH3 region results in spread of Tal1 integration regions. The integration spectra of chimeric TEs reveal the key structural variations responsible for contrasting chromatin-targeting specificities to centromeres versus gene-rich regions, which have recurrently converted during the evolution of these TEs. Our findings show the impact of centromeric chromatin on TE-mediated rapid centromere evolution, with relevance across eukaryotic genomes. en-copyright= kn-copyright= en-aut-name=TsukaharaSayuri en-aut-sei=Tsukahara en-aut-mei=Sayuri kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=BousiosAlexandros en-aut-sei=Bousios en-aut-mei=Alexandros kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=Perez-RomanEstela en-aut-sei=Perez-Roman en-aut-mei=Estela kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=YamaguchiSota en-aut-sei=Yamaguchi en-aut-mei=Sota kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=LeduqueBasile en-aut-sei=Leduque en-aut-mei=Basile kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=NakanoAimi en-aut-sei=Nakano en-aut-mei=Aimi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=NaishMatthew en-aut-sei=Naish en-aut-mei=Matthew kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= en-aut-name=OsakabeAkihisa en-aut-sei=Osakabe en-aut-mei=Akihisa kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=8 ORCID= en-aut-name=ToyodaAtsushi en-aut-sei=Toyoda en-aut-mei=Atsushi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=9 ORCID= en-aut-name=ItoHidetaka en-aut-sei=Ito en-aut-mei=Hidetaka kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=10 ORCID= en-aut-name=EderaAlejandro en-aut-sei=Edera en-aut-mei=Alejandro kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=11 ORCID= en-aut-name=TominagaSayaka en-aut-sei=Tominaga en-aut-mei=Sayaka kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=12 ORCID= en-aut-name=Juliarni en-aut-sei=Juliarni en-aut-mei= kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=13 ORCID= en-aut-name=KatoKae en-aut-sei=Kato en-aut-mei=Kae kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=14 ORCID= en-aut-name=OdaShoko en-aut-sei=Oda en-aut-mei=Shoko kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=15 ORCID= en-aut-name=InagakiSoichi en-aut-sei=Inagaki en-aut-mei=Soichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=16 ORCID= en-aut-name=LorkovićZdravko en-aut-sei=Lorković en-aut-mei=Zdravko kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=17 ORCID= en-aut-name=NagakiKiyotaka en-aut-sei=Nagaki en-aut-mei=Kiyotaka kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=18 ORCID= en-aut-name=BergerFrédéric en-aut-sei=Berger en-aut-mei=Frédéric kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=19 ORCID= en-aut-name=KawabeAkira en-aut-sei=Kawabe en-aut-mei=Akira kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=20 ORCID= en-aut-name=QuadranaLeandro en-aut-sei=Quadrana en-aut-mei=Leandro kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=21 ORCID= en-aut-name=HendersonIan en-aut-sei=Henderson en-aut-mei=Ian kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=22 ORCID= en-aut-name=KakutaniTetsuji en-aut-sei=Kakutani en-aut-mei=Tetsuji kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=23 ORCID= affil-num=1 en-affil=Department of Biological Sciences, The University of Tokyo kn-affil= affil-num=2 en-affil=School of Life Sciences, University of Sussex kn-affil= affil-num=3 en-affil=School of Life Sciences, University of Sussex kn-affil= affil-num=4 en-affil=Department of Biological Sciences, The University of Tokyo kn-affil= affil-num=5 en-affil=Institute of Plant Sciences Paris‐Saclay (IPS2), Centre National de la Recherche Scientifique, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, Université Evry, Université Paris kn-affil= affil-num=6 en-affil=Department of Biological Sciences, The University of Tokyo kn-affil= affil-num=7 en-affil=Department of Plant Sciences, University of Cambridge kn-affil= affil-num=8 en-affil=Department of Biological Sciences, The University of Tokyo kn-affil= affil-num=9 en-affil=Center for Genetic Resource Information, National Institute of Genetics kn-affil= affil-num=10 en-affil=Faculty of Science, Hokkaido University kn-affil= affil-num=11 en-affil=Institute of Plant Sciences Paris‐Saclay (IPS2), Centre National de la Recherche Scientifique, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, Université Evry, Université Paris kn-affil= affil-num=12 en-affil=Department of Biological Sciences, The University of Tokyo kn-affil= affil-num=13 en-affil=Department of Biological Sciences, The University of Tokyo kn-affil= affil-num=14 en-affil=Department of Integrated Genetics, National Institute of Genetics kn-affil= affil-num=15 en-affil=Department of Biological Sciences, The University of Tokyo kn-affil= affil-num=16 en-affil=Department of Biological Sciences, The University of Tokyo kn-affil= affil-num=17 en-affil=Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC) kn-affil= affil-num=18 en-affil=Institute of Plant Science and Resources, Okayama University kn-affil= affil-num=19 en-affil=Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC) kn-affil= affil-num=20 en-affil=Faculty of Life Sciences, Kyoto Sangyo University kn-affil= affil-num=21 en-affil=Institute of Plant Sciences Paris‐Saclay (IPS2), Centre National de la Recherche Scientifique, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, Université Evry, Université Paris kn-affil= affil-num=22 en-affil=Department of Plant Sciences, University of Cambridge kn-affil= affil-num=23 en-affil=Department of Biological Sciences, The University of Tokyo kn-affil= END start-ver=1.4 cd-journal=joma no-vol=29 cd-vols= no-issue=3-4 article-no= start-page=361 end-page=371 dt-received= dt-revised= dt-accepted= dt-pub-year=2021 dt-pub=20211014 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Effectiveness of Create ML in microscopy image classifications: a simple and inexpensive deep learning pipeline for non-data scientists en-subtitle= kn-subtitle= en-abstract= kn-abstract=Observing chromosomes is a time-consuming and labor-intensive process, and chromosomes have been analyzed manually for many years. In the last decade, automated acquisition systems for microscopic images have advanced dramatically due to advances in their controlling computer systems, and nowadays, it is possible to automatically acquire sets of tiling-images consisting of large number, more than 1000, of images from large areas of specimens. However, there has been no simple and inexpensive system to efficiently select images containing mitotic cells among these images. In this paper, a classification system of chromosomal images by deep learning artificial intelligence (AI) that can be easily handled by non-data scientists was applied. With this system, models suitable for our own samples could be easily built on a Macintosh computer with Create ML. As examples, models constructed by learning using chromosome images derived from various plant species were able to classify images containing mitotic cells among samples from plant species not used for learning in addition to samples from the species used. The system also worked for cells in tissue sections and tetrads. Since this system is inexpensive and can be easily trained via deep learning using scientists’ own samples, it can be used not only for chromosomal image analysis but also for analysis of other biology-related images. en-copyright= kn-copyright= en-aut-name=NagakiKiyotaka en-aut-sei=Nagaki en-aut-mei=Kiyotaka kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=FurutaTomoyuki en-aut-sei=Furuta en-aut-mei=Tomoyuki kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=YamajiNaoki en-aut-sei=Yamaji en-aut-mei=Naoki kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=KuniyoshiDaichi en-aut-sei=Kuniyoshi en-aut-mei=Daichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=IshiharaMegumi en-aut-sei=Ishihara en-aut-mei=Megumi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=KishimaYuji en-aut-sei=Kishima en-aut-mei=Yuji kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=MurataMinoru en-aut-sei=Murata en-aut-mei=Minoru kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= en-aut-name=HoshinoAtsushi en-aut-sei=Hoshino en-aut-mei=Atsushi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=8 ORCID= en-aut-name=TakatsukaHirotomo en-aut-sei=Takatsuka en-aut-mei=Hirotomo kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=9 ORCID= affil-num=1 en-affil=Institute of Plant Science and Resources, Okayama University kn-affil= affil-num=2 en-affil=Institute of Plant Science and Resources, Okayama University kn-affil= affil-num=3 en-affil=Institute of Plant Science and Resources, Okayama University kn-affil= affil-num=4 en-affil=Laboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University kn-affil= affil-num=5 en-affil=Laboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University kn-affil= affil-num=6 en-affil=Laboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University kn-affil= affil-num=7 en-affil=Department of Agricultural and Food Science, Universiti Tunku Abdul Rahman kn-affil= affil-num=8 en-affil=National Institute for Basic Biology kn-affil= affil-num=9 en-affil=Graduate School of Science and Technology, Nara Institute of Science and Technology kn-affil= en-keyword=Machine learning kn-keyword=Machine learning en-keyword=deep learning kn-keyword=deep learning en-keyword=mitotic cell kn-keyword=mitotic cell en-keyword=chromosome kn-keyword=chromosome en-keyword=tetrad kn-keyword=tetrad en-keyword=microscope kn-keyword=microscope END