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
이예지 (National Institute of Agricultural Sciences RDA Korea) Nam-In Hyung (Sangmyung University) 김태호 (National Institute of Agricultural Sciences RDA Korea)
저널정보
한국육종학회 Plant Breeding and Biotechnology Plant Breeding and Biotechnology Vol.8 No.3
발행연도
2020.1
수록면
293 - 306 (14page)

이용수

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

초록· 키워드

오류제보하기
High-throughput genotyping has substantially advanced the quality and accuracy of single nucleotide polymorphism (SNP) discovery and provided an effective way to interpret phenotypic variations in a mapping population. High-resolution quantitative trait locus (QTL) mapping is important for understanding agricultural traits. However, constructing a high-resolution map without sufficient markers to detect QTLs/genes of agronomically important traits is laborious and time consuming. In this study, 160 recombinant inbred lines (RILs) derived from a cross between Milyang23 and Gihobyeo were re-sequenced, and their SNPs were used for high-resolution QTL mapping of yield-related traits. A total of 1,850,671 high-quality SNPs from RILs were detected, and 3,563 bins were used as genetic markers to construct a high-resolution genetic map using the sliding window approach. The total genetic distance was 1,278.62 cM. Using the QTL analysis, we identified 35 QTLs controlling six yield traits, namely, culm length, panicle length, panicle number per plant, primary branch number per panicle, grain number per plant, and 100-grain weight. In addition, we detected major QTLs associated with culm length and grain number, and compared their physical distances using a conventional genetic map. These results showed that rapid, high-resolution QTL mapping using high-quality SNPs as bin markers is a powerful tool for finemapping and cloning important QTLs/genes.

목차

등록된 정보가 없습니다.

참고문헌 (39)

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