메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
Singh Devika (Georgia Institute of Technology) Yi Soojin V. (Georgia Institute of Technology)
저널정보
대한생화학·분자생물학회 Experimental and Molecular Medicine Experimental and Molecular Medicine 제53권
발행연도
2021.4
수록면
1 - 11 (11page)
DOI
10.1038/s12276-021-00604-z

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the ongoing global outbreak of a coronavirus disease (herein referred to as COVID-19). Other viruses in the same phylogenetic group have been responsible for previous regional outbreaks, including SARS and MERS. SARS-CoV-2 has a zoonotic origin, similar to the causative viruses of these previous outbreaks. The repetitive introduction of animal viruses into human populations resulting in disease outbreaks suggests that similar future epidemics are inevitable. Therefore, understanding the molecular origin and ongoing evolution of SARS-CoV-2 will provide critical insights for preparing for and preventing future outbreaks. A key feature of SARS-CoV-2 is its propensity for genetic recombination across host species boundaries. Consequently, the genome of SARS-CoV-2 harbors signatures of multiple recombination events, likely encompassing multiple species and broad geographic regions. Other regions of the SARS-CoV-2 genome show the impact of purifying selection. The spike (S) protein of SARS-CoV-2, which enables the virus to enter host cells, exhibits signatures of both purifying selection and ancestral recombination events, leading to an effective S protein capable of infecting human and many other mammalian cells. The global spread and explosive growth of the SARS-CoV-2 population (within human hosts) has contributed additional mutational variability into this genome, increasing opportunities for future recombination.

목차

등록된 정보가 없습니다.

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0