High-dimensional and large-scale phenotyping of yeast mutants

被引:219
|
作者
Ohya, Y
Sese, J
Yukawa, M
Sano, F
Nakatani, Y
Saito, TL
Saka, A
Fukuda, T
Ishihara, S
Oka, S
Suzuki, G
Watanabe, M
Hirata, A
Ohtani, M
Sawai, H
Fraysse, N
Latgé, JP
François, JM
Aebi, M
Tanaka, S
Muramatsu, S
Araki, H
Sonoike, K
Nogami, S
Morishita, S
机构
[1] Univ Tokyo, Grad Sch Frontier Sci, Dept Integrated Biosci, Kashiwa, Chiba 2778562, Japan
[2] Univ Tokyo, Grad Sch Frontier Sci, Dept Computat Biol, Kashiwa, Chiba 2778562, Japan
[3] Japan Sci & Technol Corp, Inst Bioinformat & Res & Dev, Chiyoda Ku, Tokyo 1028666, Japan
[4] Univ Tokyo, Dept Comp Sci, Grad Sch Informat Sci & Technol, Bunkyo Ku, Tokyo 1130033, Japan
[5] Inst Pasteur, Unite Aspergillus, F-75015 Paris, France
[6] CNRS, Ctr Bioingn Gilbert Durand, UMR 5504, INRA, F-31077 Toulouse, France
[7] ETH, ETH Honggerberg, Inst Microbiol, CH-8093 Zurich, Switzerland
[8] Natl Inst Genet, Div Microbial Genet, Mishima, Shizuoka 4118540, Japan
关键词
cell morphology; functional genomics; high-dimensional phenotyping; phenome;
D O I
10.1073/pnas.0509436102
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
One of the most powerful techniques for attributing functions to genes in uni- and multicellular organisms is comprehensive analysis of mutant traits. In this study, systematic and quantitative analyses of mutant traits are achieved in the budding yeast Saccharomyces cerevisiae by investigating morphological phenotypes. Analysis of fluorescent microscopic images of triple-stained cells makes it possible to treat morphological variations as quantitative traits. Deletion of nearly half of the yeast genes not essential for growth affects these morphological traits. Similar morphological phenotypes are caused by deletions of functionally related genes, enabling a functional assignment of a locus to a specific cellular pathway. The high-dimensional phenotypic analysis of defined yeast mutant strains provides another step toward attributing gene function to all of the genes in the yeast genome.
引用
收藏
页码:19015 / 19020
页数:6
相关论文
共 50 条
  • [41] An improved method of locality sensitive hashing for indexing large-scale and high-dimensional features
    Gu, Xiaoguang
    Zhang, Yongdong
    Zhang, Lei
    Zhang, Dongming
    Li, Jintao
    SIGNAL PROCESSING, 2013, 93 (08) : 2244 - 2255
  • [42] Large-Scale Automatic Feature Selection for Biomarker Discovery in High-Dimensional OMICs Data
    Leclercq, Mickael
    Vittrant, Benjamin
    Martin-Magniette, Marie Laure
    Boyer, Marie Pier Scott
    Perin, Olivier
    Bergeron, Alain
    Fradet, Yves
    Droit, Arnaud
    FRONTIERS IN GENETICS, 2019, 10
  • [43] Fast Low-rank Metric Learning for Large-scale and High-dimensional Data
    Liu, Han
    Han, Zhizhong
    Liu, Yu-Shen
    Gu, Ming
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), 2019, 32
  • [44] Grid-based indexing and search algorithms for large-scale and high-dimensional data
    Yang, Chuanfu
    Li, Zhiyang
    Qu, Wenyu
    Liu, Zhaobin
    Qi, Heng
    2017 14TH INTERNATIONAL SYMPOSIUM ON PERVASIVE SYSTEMS, ALGORITHMS AND NETWORKS & 2017 11TH INTERNATIONAL CONFERENCE ON FRONTIER OF COMPUTER SCIENCE AND TECHNOLOGY & 2017 THIRD INTERNATIONAL SYMPOSIUM OF CREATIVE COMPUTING (ISPAN-FCST-ISCC), 2017, : 46 - 51
  • [45] Rejoinder on: statistical inference and large-scale multiple testing for high-dimensional regression models
    T. Tony Cai
    Zijian Guo
    Yin Xia
    TEST, 2023, 32 : 1187 - 1194
  • [46] Communication-efficient distributed estimation for high-dimensional large-scale linear regression
    Zhan Liu
    Xiaoluo Zhao
    Yingli Pan
    Metrika, 2023, 86 : 455 - 485
  • [47] Machine learning of large-scale spatial distributions of wild turkeys with high-dimensional environmental data
    Farrell, Annie
    Wang, Guiming
    Rush, Scott A.
    Martin, James A.
    Belant, Jerrold L.
    Butler, Adam B.
    Godwin, Dave
    ECOLOGY AND EVOLUTION, 2019, 9 (10): : 5938 - 5949
  • [48] BSSReduce an O(|U|) Incremental Feature Selection Approach for Large-Scale and High-Dimensional Data
    Gong, Ke
    Wang, Yong
    Xu, Maozeng
    Xiao, Zhi
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26 (06) : 3356 - 3367
  • [49] Text Relevance Analysis Method over Large-Scale High-Dimensional Text Data Processing
    Wang, Ling
    Ding, Wei
    Zhou, Tie Hua
    Ryu, Keun Ho
    COMPUTATIONAL COLLECTIVE INTELLIGENCE (ICCCI 2015), PT I, 2015, 9329 : 371 - 379
  • [50] High-dimensional large-scale mixed-type data imputation under missing at random
    Liu, Wei
    Li, Guizhen
    Zhou, Ling
    Luo, Lan
    SCIENCE CHINA-MATHEMATICS, 2025, 68 (04) : 969 - 1000