複数の信号の複合は,陽性選択の領域における因果的変異を区別する

Sharon R Grossman¹, Ilya Shlyakhter, Ilya Shylakhter

¹Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. shari.grossman@post.harvard.edu

Science (New York, N.Y.)

|January 9, 2010

まとめ

科学者たちは,複数の信号 (CMS) から構成された新しい方法を開発し,ヒトゲノムで最近肯定的な自然選択を経験した特定の遺伝的変異を特定し,解像度を100倍改善しました.

科学分野:

人間の遺伝学人間の遺伝学
進化生物学の進化生物学について
ゲノミクスゲノミクスとは

背景:

人間のゲノムには,遺伝的変異パターンが多くあり,近年の肯定的な自然選択を示唆している.
これらの選択信号に起因する特定の遺伝子と有利な突然変異を特定することは,遺伝学における重要な課題です.

研究の目的:

最近の陽性自然選択の下で正確な遺伝子変異を特定するための高解像度メソッドを開発する.
ヒトゲノム内の集団特有の選択信号の局所化を改善する.

主な方法:

多数の信号の複合 (CMS) と呼ばれる新しい計算方法を開発しました.
CMSは,解像度を高めるために,選択信号の複数の統計テストを統合しています.
国際ハプロタイプマップで特定された候補地域に対してCMSを適用した.

主要な成果:

集団特有の選択信号を55キロベースの中央領域に局所化し,解像度が100倍に増加しました.
自然選択と関連した既知のおよび新しい因果変異の両方を成功裏に特定しました.
より広いゲノム領域だけでなく,精密な進化的に選択された変異を特定するCMSの能力を実証しました.

結論:

多数の信号 (CMS) の複合法により,最近の陽性選択下で遺伝的変異を特定する精度が大幅に向上します.
CMSは,特定の有利な突然変異とその基礎となる遺伝子の発見を容易にし,人間の進化に関する理解を深める.
このアプローチは,ヒト集団における適応の遺伝的基盤を解剖するための強力なツールを提供します.

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