The Rice Genome Research Project in Japan performs genome sequencing and comprehensive expression profiling, constructs genetic and physical maps, collects full-length cDNAs and generates mutant lines, all aimed at improving the breeding of the rice plant as a food source. The National Institute of Agrobiological Sciences in Tsukuba, Japan, has accumulated numerous rice biological resources and has already successfully produced a high-quality genome sequence, a high-density genetic map with 3000 markers, 30,000 full-length cDNAs, over 700 expression profiles with a 9000 cDNA microarray and 15,000 flanking sequences with Tos17 insertions in about 3765 mutant lines from about 50,000 transposon insertion lines. These resources are available in the public domain. A new unification tool for functional genomics, called Rice PIPELINE, has also been developed for the dynamic collection and compilation of genomics data (genome sequences, full-length cDNAs, gene expression profiles, mutant lines, cis elements) from various databases. The mission of Rice PIPELINE is to provide a unique scientific resource that pools publicly available rice genomic data for search by clone sequence, clone name, GenBank accession number, or keyword. The web-based form of Rice PIPELINE is available at http://cdna01.dna.affrc.go.jp/PIPE/.
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http://dx.doi.org/10.1093/nar/gkh001 | DOI Listing |
Mol Genet Genomics
January 2025
Department of Botany, Biology Institute, UnB, Brasília, DF, 70910-900, Brazil.
Precursors of microRNAs (pre-miRNAs) are less used in silico to mine miRNAs. This study developed PmiR-Select based on covariance models (CMs) to identify new pre-miRNAs, detecting conserved secondary structural features across RNA sequences and eliminating the redundancy. The pipeline preceded PmiR-Select filtered 20% plant pre-miRNAs (from 38589 to 8677) from miRBase.
View Article and Find Full Text PDFInfect Control Hosp Epidemiol
December 2024
Department of Infectious Diseases, Infection Control, and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Objective: Whole genome sequencing (WGS) can help identify transmission of pathogens causing healthcare-associated infections (HAIs). However, the current gold standard of short-read, Illumina-based WGS is labor and time intensive. Given recent improvements in long-read Oxford Nanopore Technologies (ONT) sequencing, we sought to establish a low resource approach providing accurate WGS-pathogen comparison within a time frame allowing for infection prevention and control (IPC) interventions.
View Article and Find Full Text PDFPlant Physiol Biochem
December 2024
Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, Liaoning, China. Electronic address:
To explore the bio-effects during Moon exploration missions, we utilized the Chang'E 5 probe to carry the seeds of Oryza. Sativa L., which were later returned to Earth after 23 days in lunar orbit and planted in an artificial climate chamber.
View Article and Find Full Text PDFJ Hazard Mater
December 2024
School of Earth sciences and Resources, China University of Geosciences (Beijing), Beijing 100083, China.
Rapid and accurate prediction of rice Cd (rCd) and rice As (rAs) bioaccumulation are important for assessing the safe utilization of rice. Currently, there is lack of comprehensive and systematic exploration of the factors of rCd and rAs. Herein, ensemble learning (EL) was first used to analysis the 23 factors in 8 categories (heavy metal pollution characteristics, soil properties, geographical characteristics, meteorological factors, socio-economic factors, environmental factors, rice type, and nutrient element) in typical regions of China based on the results of 193 research papers from 2000 to 2024 in Web of Science database.
View Article and Find Full Text PDFSci Rep
November 2024
USDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA.
TV viewing is associated with health risks, but existing measures of TV viewing are imprecise due to relying on self-report. We developed the Family Level Assessment of Screen use in the Home (FLASH)-TV, a machine learning pipeline with state-of-the-art computer vision methods to measure children's TV viewing. In three studies, lab pilot (n = 10), lab validation (n = 30), and home validation (n = 20), we tested the validity of FLASH-TV 3.
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