Mongolian oak (Quercus mongolica Fisch.) is an ecologically and economically important white oak species native to and widespread in the temperate zone of East Asia. Here, we present a chromosome-scale reference genome assembly of Q. mongolica, a representative white oak species, by combining Illumina and PacBio data with Hi-C mapping technologies that is the first reference genome created for an Asian oak. Our results showed that the PacBio draft genome size was 809.84 Mb, with a BUSCO complete gene percentage of 92.71%. Hi-C scaffolding anchored 774.59 Mb contigs (95.65% of draft assembly) onto 12 pseudochromosomes. The contig N50 and scaffold N50 were 2.64 and 66.74 Mb, respectively. Of the 36,553 protein-coding genes predicted in the study, approximately 95% had functional annotations in public databases. A total of 435.34 Mb (53.75% of the genome) of repetitive sequences were predicted in the assembled genome. Genome evolution analysis showed that Q. mongolica is closely related to Q. robur from Europe, and they shared a common ancestor ~11.8 million years ago (Ma). Gene family evolution analysis of Q. mongolica revealed that the nucleotide-binding site (NBS)-encoding gene family related to disease resistance was significantly contracted, whereas the ECERIFERUM 1 (CER1) homologous genes related to cuticular wax biosynthesis was significantly expanded. This pioneering Asian oak genome resource represents an important supplement to the oak genomics community and will improve our understanding of Asian white oak biology and evolution.
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http://dx.doi.org/10.1111/1755-0998.13616 | DOI Listing |
Am J Perinatol
January 2025
Department of Maternal Fetal Medicine, Advocate Aurora Health Inc, Oak Lawn, United States.
Objective The impact of type 1 DM (T1DM) on thromboembolism in pregnancy is uncertain. We hypothesized that T1DM is associated with higher rates of thrombotic events during pregnancy and the postpartum period. Study Design This is a retrospective cohort study utilizing the National Inpatient Sample database from HCUP/AHRQ for 2017-2019.
View Article and Find Full Text PDFEnviron Microbiol
January 2025
Forestry and Forest Products Research Institute, Tsukuba, Ibaraki, Japan.
Oak wilt causes severe dieback of Quercus serrata, a dominant tree species in the lowlands across Japan. This study evaluated the effects of oak wilt on the wood-inhabiting fungal community and the decay rate of deadwood using a field monitoring experiment. We analysed the fungal metabarcoding community from 1200 wood samples obtained from 120 experimental logs from three forest sites at five different time points during the initial 1.
View Article and Find Full Text PDFCancer Epidemiol
December 2024
Division of Cancer Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, United States.
Introduction: Variations in cervical cancer incidence rates and trends have been reported by sociodemographic characteristics. However, research on economic characteristics is limited especially among younger women in the United States.
Methods: We analyzed United States Cancer Statistics data to examine age-standardized cervical cancer incidence rates among women aged 15-29 years during 2007-2020.
Nat Commun
December 2024
Institute for Quantum Computing, University of Waterloo, Waterloo, ON, Canada.
Methods to prepare and characterize neutron helical waves carrying orbital angular momentum (OAM) were recently demonstrated at small-angle neutron scattering (SANS) facilities. These methods enable access to the neutron orbital degree of freedom which provides new avenues of exploration in fundamental science experiments as well as in material characterization applications. However, it remains a challenge to recover phase profiles from SANS measurements.
View Article and Find Full Text PDFJ Pathol Inform
January 2025
U.S. Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging, Diagnostics, and Software Reliability, Silver Spring, MD, United States of America.
Objective: With the increasing energy surrounding the development of artificial intelligence and machine learning (AI/ML) models, the use of the same external validation dataset by various developers allows for a direct comparison of model performance. Through our High Throughput Truthing project, we are creating a validation dataset for AI/ML models trained in the assessment of stromal tumor-infiltrating lymphocytes (sTILs) in triple negative breast cancer (TNBC).
Materials And Methods: We obtained clinical metadata for hematoxylin and eosin-stained glass slides and corresponding scanned whole slide images (WSIs) of TNBC core biopsies from two US academic medical centers.
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