一個由法國,、美國、澳大利亞等國科學(xué)家組成的研究小組日前為小麥的一個基因組繪制出了首幅物理圖譜,，這一成果將有助于科學(xué)家培育出更高產(chǎn)和抗旱的小麥新品種,。
基因組物理圖譜是指有關(guān)構(gòu)成基因組的全部基因的排列和間距的信息，它是通過對構(gòu)成基因組的DNA分子進(jìn)行測定而繪制的,。繪制物理圖譜的目的是把有關(guān)基因的遺傳信息及其在每條染色體上的相對位置線性而系統(tǒng)地排列出來,。
這項(xiàng)研究由法國國家農(nóng)藝研究所專家克萊蒙·費(fèi)朗牽頭完成。據(jù)介紹,，小麥的基因組不但數(shù)量多,，且結(jié)構(gòu)復(fù)雜，因此對其進(jìn)行測序被視為“不可能完成的任務(wù)”,。小麥的染色體共含有170億對堿基,，是水稻的約40倍，是人體的約5倍,，因此測序工作進(jìn)展相對緩慢,。
研究人員介紹說，繪制基因組物理圖譜是為基因組測序的基礎(chǔ),，所以他們從小麥最大的染色體3B入手,。這條染色體含有10億對堿基和1036個基因重疊組，科學(xué)家們通過對基因進(jìn)行標(biāo)記,，成功地將其排列順序,，并繪出了物理圖譜。
研究人員表示,，物理圖譜能幫助人們迅速鎖定控制小麥產(chǎn)量和數(shù)量的基因,，從而對作物的品種進(jìn)行改良?？茖W(xué)家們已根據(jù)該圖譜確定了一個抗黑銹病基因的具體位置,。黑銹病會嚴(yán)重影響小麥產(chǎn)量，如能培育出抗該病的新品種，將有望大幅提高小麥產(chǎn)量,。
這一研究成果已發(fā)表在10月3日出版的美國《科學(xué)》（Science）雜志上。（生物谷Bioon.com）
生物谷推薦原始出處：
Science,，Vol. 322. no. 5898, pp. 101 - 104,，Etienne Paux，Catherine Feuillet
A Physical Map of the 1-Gigabase Bread Wheat Chromosome 3B
Etienne Paux,1 Pierre Sourdille,1 Jérôme Salse,1 Cyrille Saintenac,1 Frédéric Choulet,1 Philippe Leroy,1Abraham Korol,2 Monika Michalak,3 Shahryar Kianian,3 Wolfgang Spielmeyer,4 Evans Lagudah,4Daryl Somers,5 Andrzej Kilian,6 Michael Alaux,7 Sonia Vautrin,8 Hélène Bergès,8 Kellye Eversole,9Rudi Appels,10 Jan Safar,11 Hana Simkova,11 Jaroslav Dolezel,11 Michel Bernard,1 Catherine Feuillet1
As the staple food for 35% of the world's population, wheat is one of the most important crop species. To date, sequence-based tools to accelerate wheat improvement are lacking. As part of the international effort to sequence the 17–billion–base-pair hexaploid bread wheat genome (2n = 6x = 42 chromosomes), we constructed a bacterial artificial chromosome (BAC)–based integrated physical map of the largest chromosome, 3B, that alone is 995 megabases. A chromosome-specific BAC library was used to assemble 82% of the chromosome into 1036 contigs that were anchored with 1443 molecular markers, providing a major resource for genetic and genomic studies. This physical map establishes a template for the remaining wheat chromosomes and demonstrates the feasibility of constructing physical maps in large, complex, polyploid genomes with a chromosome-based approach.
1 Institut National de la Recherche Agronomique, Université Blaise Pascal (INRA-UBP), UMR 1095, Genetics Diversity and Ecophysiology of Cereals, Clermont-Ferrand, France.
2 Institute of Evolution, University of Haifa, Haifa, Israel.
3 Department of Plant Sciences, North Dakota State University, Fargo, ND, USA.
4 Commonwealth Scientific and Industrial Research Organization Plant Industry, Canberra, Australia.
5 Agriculture and Agri-Food Canada, Cereal Research Centre, Winnipeg, Canada.
6 Diversity Arrays Technology, Yarralumla, Canberra, Australia.
7 INRA–Unité de Recherches en Génomique-Info, Versailles, France.
8 INRA–Centre National de Ressources Génomiques Végétales, Toulouse, France.
9 International Wheat Genome Sequencing Consortium, Eversole Associates, Bethesda, MD, USA.
10 Centre for Comparative Genomics, Murdoch University, Perth, Australia.
11 Laboratory of Molecular Cytogenetics and Cytometry, Institute of Experimental Botany, Olomouc, Czech Republic.
