Ancestral haplotype reconstruction in endogamous populations using identity-by-descent.
Ancestral haplotype reconstruction in endogamous populations using identity-by-descent.
复制标题
利用世系认同重建内婚群体的祖先单倍型。
DOI：
10.1371/journal.pcbi.1008638
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发表时间：
2021-03
影响因子：
4.3
通讯作者：
Mathieson S
中科院分区：
文献类型：
--
作者：
Finke K;Kourakos M;Brown G;Dang HT;Tan SJS;Simons YB;Ramdas S;Schäffer AA;Kember RL;Bućan M;Mathieson S
在这项工作中，我们开发了一种新的算法，用于重建祖先个体的基因组，从当代个体的基因型或序列数据和家庭关系的扩展谱系。一个具有每个个体完整基因组的系谱能够研究等位基因频率动态和跨代单倍型多样性，包括偏离中性，如传递失真。在研究遗传性疾病时，祖先单倍型可用于增强全基因组关联研究和跟踪疾病遗传模式。我们的重建算法的构建块是两个或多个基因分型个体之间共享的血统识别（IBD）片段。该方法在鉴定每个IBD区段的来源和组装置于每个祖先个体内的IBD区段之间交替。与以前的方法不同，我们的方法能够适应复杂的谱系结构，数百个个体在数百万个SNP上进行基因分型。我们应用我们的方法，从兰开斯特，宾夕法尼亚州，其创始人来到北美从欧洲在18世纪初世纪的旧秩序阿米什血统。该家系包括过去12代的1338个个体，其中394个具有基因型数据。重建的动机是通过追踪单倍型随时间的传播来了解疾病在家族中分离的遗传基础。使用我们的算法线程，我们能够重建平均每个染色体224个祖先个体。对于这些祖先个体，我们平均重建了79%的单倍型。我们还确定了16号染色体上的一个区域，这是很难重建，我们发现，该地区窝藏一个短的阿米什特定的拷贝数变异和基因HYDIN。线索是为同族通婚的人群开发的，但也可以应用于任何广泛的系谱，最近几代人的基因分型。我们预计，这种类型的实际祖先重建将变得更加普遍和必要的了解罕见和复杂的遗传性疾病在大家庭。在分析复杂的遗传性状时，来自大家族多代的基因组数据增加了可用于统计推断的信息量。然而，通常只有来自系谱的最近几代的基因组数据是可用的，因为祖先个体已经死亡。在这项工作中，我们提出了一个算法，称为线程，重建祖先个体的基因组，给定一个复杂的谱系和基因组数据，从最近几代。以前的方法无法适应大型数据集（无论是在网站和个人方面），简化了对谱系结构的假设，或者没有将重建的序列与特定的个人联系起来。我们应用线程到一个复杂的旧秩序阿米什谱系1338人，394与基因型数据。
In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies and track disease inheritance patterns. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between identifying a source for each IBD segment and assembling IBD segments placed within each ancestral individual. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs. We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to North America from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 12 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 224 ancestral individuals per chromosome. For these ancestral individuals, on average we reconstruct 79% of their haplotypes. We also identify a region on chromosome 16 that is difficult to reconstruct—we find that this region harbors a short Amish-specific copy number variation and the gene HYDIN. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families. When analyzing complex heritable traits, genomic data from many generations of an extended family increases the amount of information available for statistical inference. However, typically only genomic data from the recent generations of a pedigree are available, as ancestral individuals are deceased. In this work we present an algorithm, called thread, for reconstructing the genomes of ancestral individuals, given a complex pedigree and genomic data from the recent generations. Previous approaches have not been able to accommodate large datasets (both in terms of sites and individuals), made simplifying assumptions about pedigree structure, or did not tie reconstructed sequences back to specific individuals. We apply thread to a complex Old Order Amish pedigree of 1338 individuals, 394 with genotype data.
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影响因子：
64.8
作者：
Frazer, Kelly A.;Ballinger, Dennis G.;Cox, David R.;Hinds, David A.;Stuve, Laura L.;Gibbs, Richard A.;Belmont, John W.;Boudreau, Andrew;Hardenbol, Paul;Leal, Suzanne M.;Pasternak, Shiran;Wheeler, David A.;Willis, Thomas D.;Yu, Fuli;Yang, Huanming;Zeng, Changqing;Gao, Yang;Hu, Haoran;Hu, Weitao;Li, Chaohua;Lin, Wei;Liu, Siqi;Pan, Hao;Tang, Xiaoli;Wang, Jian;Wang, Wei;Yu, Jun;Zhang, Bo;Zhang, Qingrun;Zhao, Hongbin;Zhao, Hui;Zhou, Jun;Gabriel, Stacey B.;Barry, Rachel;Blumenstiel, Brendan;Camargo, Amy;Defelice, Matthew;Faggart, Maura;Goyette, Mary;Gupta, Supriya;Moore, Jamie;Nguyen, Huy;Onofrio, Robert C.;Parkin, Melissa;Roy, Jessica;Stahl, Erich;Winchester, Ellen;Ziaugra, Liuda;Altshuler, David;Shen, Yan;Yao, Zhijian;Huang, Wei;Chu, Xun;He, Yungang;Jin, Li;Liu, Yangfan;Shen, Yayun;Sun, Weiwei;Wang, Haifeng;Wang, Yi;Wang, Ying;Xiong, Xiaoyan;Xu, Liang;Waye, Mary M. Y.;Tsui, Stephen K. W.;Wong, J. Tze-Fei;Galver, Luana M.;Fan, Jian-Bing;Gunderson, Kevin;Murray, Sarah S.;Oliphant, Arnold R.;Chee, Mark S.;Montpetit, Alexandre;Chagnon, Fanny;Ferretti, Vincent;Leboeuf, Martin;Olivier, Jean-Franccois;Phillips, Michael S.;Roumy, Stephanie;Sallee, Clementine;Verner, Andrei;Hudson, Thomas J.;Kwok, Pui-Yan;Cai, Dongmei;Koboldt, Daniel C.;Miller, Raymond D.;Pawlikowska, Ludmila;Taillon-Miller, Patricia;Xiao, Ming;Tsui, Lap-Chee;Mak, William;Song, You Qiang;Tam, Paul K. H.;Nakamura, Yusuke;Kawaguchi, Takahisa;Kitamoto, Takuya;Morizono, Takashi;Nagashima, Atsushi;Ohnishi, Yozo;Sekine, Akihiro;Tanaka, Toshihiro;Tsunoda, Tatsuhiko;Deloukas, Panos;Bird, Christine P.;Delgado, Marcos;Dermitzakis, Emmanouil T.;Gwilliam, Rhian;Hunt, Sarah;Morrison, Jonathan;Powell, Don;Stranger, Barbara E.;Whittaker, Pamela;Bentley, David R.;Daly, Mark J.;de Bakker, Paul I. W.;Barrett, Jeff;Chretien, Yves R.;Maller, Julian;McCarroll, Steve;Patterson, Nick;Pe'er, Itsik;Price, Alkes;Purcell, Shaun;Richter, Daniel J.;Sabeti, Pardis;Saxena, Richa;Schaffner, Stephen F.;Sham, Pak C.;Varilly, Patrick;Altshuler, David;Stein, Lincoln D.;Krishnan, Lalitha;Smith, Albert Vernon;Tello-Ruiz, Marcela K.;Thorisson, Gudmundur A.;Chakravarti, Aravinda;Chen, Peter E.;Cutler, David J.;Kashuk, Carl S.;Lin, Shin;Abecasis, Goncalo R.;Guan, Weihua;Li, Yun;Munro, Heather M.;Qin, Zhaohui Steve;Thomas, Daryl J.;McVean, Gilean;Auton, Adam;Bottolo, Leonardo;Cardin, Niall;Eyheramendy, Susana;Freeman, Colin;Marchini, Jonathan;Myers, Simon;Spencer, Chris;Stephens, Matthew;Donnelly, Peter;Cardon, Lon R.;Clarke, Geraldine;Evans, David M.;Morris, Andrew P.;Weir, Bruce S.;Tsunoda, Tatsuhiko;Johnson, Todd A.;Mullikin, James C.;Sherry, Stephen T.;Feolo, Michael;Skol, Andrew
通讯作者：
Skol, Andrew
影响因子：
1.7
作者：
He, Dan;Wang, Zhanyong;Eskin, Eleazar
通讯作者：
Eskin, Eleazar
DOI：
10.1080/01621459.1995.10476590
发表时间：
1995-09-01
影响因子：
3.7
作者：
GEYER, CJ;THOMPSON, EA
通讯作者：
THOMPSON, EA
影响因子：
7
作者：
Gusev, Alexander;Lowe, Jennifer K.;Pe'er, Itsik
通讯作者：
Pe'er, Itsik
影响因子：
30.8
作者：
Abecasis, GR;Cherny, SS;Cardon, LR
通讯作者：
Cardon, LR