J
Ja Young Shin
Researcher at Rural Development Administration
Publications - 3
Citations - 166
Ja Young Shin is an academic researcher from Rural Development Administration. The author has contributed to research in topics: Genome & Brassica rapa. The author has an hindex of 3, co-authored 3 publications receiving 154 citations.
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Journal ArticleDOI
Sequence and structure of Brassica rapa chromosome A3
Jeong Hwan Mun,Soo Jin Kwon,Young Joo Seol,Jin A Kim,Mina Jin,Jung Sun Kim,Myung-Ho Lim,Soo In Lee,Joon Ki Hong,Tae-Ho Park,Sang Choon Lee,Beom Jin Kim,Mi Suk Seo,Seunghoon Baek,Min Jee Lee,Ja Young Shin,Jang Ho Hahn,Yoon-Jung Hwang,Ki-Byung Lim,Jee Young Park,Jonghoon Lee,Tae-Jin Yang,Hee Ju Yu,Ik-Young Choi,Beom-Soon Choi,Su Ryun Choi,Nirala Ramchiary,Yong Pyo Lim,Fiona Fraser,Nizar Drou,Eleni Soumpourou,Martin Trick,Ian Bancroft,Andrew G. Sharpe,Isobel A. P. Parkin,Jacqueline Batley,Dave Edwards,Beom Seok Park +37 more
TL;DR: The near-complete chromosome sequence from a dicotyledonous crop species provides an example of the complexity of genome evolution following polyploidy and provides a benchmark for the performance of whole genome shotgun approaches presently being applied in B. rapa and other species with complex genomes.
Journal ArticleDOI
Auxin response factor gene family in Brassica rapa: genomic organization, divergence, expression, and evolution.
TL;DR: This study identified the auxin response factor (ARF) gene family, which is one of the key regulators of auxin-mediated plant growth and development in the B. rapa genome, and will provide a fundamental basis for the modification and evolution of the gene family after a polyploidy event, as well as a functional study of ARF genes in a polyPLoidy crop species.
Journal ArticleDOI
Identification and profiling of novel microRNAs in the Brassica rapa genome based on small RNA deep sequencing
TL;DR: This is the first report to identify novelMiRNAs from Brassica crops using genome-wide high throughput techniques and the combination of computational methods and small RNA deep sequencing provides robust predictions of miRNAs in the genome.