Distinguishing functional polymorphism from random variation in the sequences of >10,000 HLA-A, -B and -C alleles.
Distinguishing functional polymorphism from random variation in the sequences of >10,000 HLA-A, -B and -C alleles.
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在> 10,000 HLA -A，-b和-c等位基因的序列中区分功能性多态性与随机变化。
DOI：
10.1371/journal.pgen.1006862
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发表时间：
2017-06
期刊：
影响因子：
4.5
通讯作者：
Parham P
中科院分区：
文献类型：
--
作者：
Robinson J;Guethlein LA;Cereb N;Yang SY;Norman PJ;Marsh SGE;Parham P
HLA I类糖蛋白含有结合肽抗原和接合淋巴细胞受体的功能位点。最近，基于序列的HLA分型的临床应用已经发现了前所未有数量的新的HLA I类等位基因。在这里，我们定义了3，489个HLA-A，4，356个HLA-B和3，111个HLA-C等位基因变异的性质和程度。这种分析需要开发一套具有普遍适用性的方法，用于比较和分析大量同源序列。在HLA-A、-B和-C的多态性α1和α2结构域的每个位置上至少存在三个氨基酸取代。少数位置对于“第二”最频繁的核苷酸具有>1%的发生率，包括HLA-A中的70个位置、HLA-B中的85个位置和HLA-C中的54个位置。这些位置中的大多数具有三个或四个替代核苷酸。这些位置经过阳性选择，对应于肽和受体的结合位点。大多数HLA I类等位基因（>80%）非常罕见，通常在一个人或一个家庭中鉴定，它们与更古老，更常见的等位基因的点突变不同。这些具有单核苷酸多态性的等位基因反映了种系突变率。它们的频率预测人类群体具有800 - 900万HLA I类变体。人类群体的常见等位基因包括42个核心等位基因，其代表所有选择的多态性，以及具有该多态性的重组体。HLA复合体是人类基因组中含有免疫系统基因的区域。我们的研究涉及那些协调防御病毒感染的HLA基因。HLA基因与其他人类基因的区别在于其在个体、家族和群体中的广泛变异。这种基因变异的一个好处是增加了对付病毒的武器的深度和广度;另一个好处是阻止了感染在家庭和社区内的传播。HLA变异的一个缺点是，不同HLA类型的供体和患者之间的骨髓移植会引发免疫反应，从而攻击并杀死患者。对于一些患者，HLA相同的家庭成员可以是供体，但对于其他患者，需要寻找不相关的HLA相同的供体。促进这些搜索的是登记处，登记处列出了数百万可能的供体，其HLA类型是通过基因测序确定的。在过去的十年中，这一努力使测序的HLA变体数量呈指数增长。这为我们提供了前所未有的机会，可以比较超过10，000个序列，并区分对免疫功能重要的变异方面。然而，首先，我们需要开发能够处理大量数据的软件。
HLA class I glycoproteins contain the functional sites that bind peptide antigens and engage lymphocyte receptors. Recently, clinical application of sequence-based HLA typing has uncovered an unprecedented number of novel HLA class I alleles. Here we define the nature and extent of the variation in 3,489 HLA-A, 4,356 HLA-B and 3,111 HLA-C alleles. This analysis required development of suites of methods, having general applicability, for comparing and analyzing large numbers of homologous sequences. At least three amino-acid substitutions are present at every position in the polymorphic α1 and α2 domains of HLA-A, -B and -C. A minority of positions have an incidence >1% for the ‘second’ most frequent nucleotide, comprising 70 positions in HLA-A, 85 in HLA-B and 54 in HLA-C. The majority of these positions have three or four alternative nucleotides. These positions were subject to positive selection and correspond to binding sites for peptides and receptors. Most alleles of HLA class I (>80%) are very rare, often identified in one person or family, and they differ by point mutation from older, more common alleles. These alleles with single nucleotide polymorphisms reflect the germ-line mutation rate. Their frequency predicts the human population harbors 8–9 million HLA class I variants. The common alleles of human populations comprise 42 core alleles, which represent all selected polymorphism, and recombinants that have assorted this polymorphism. The HLA complex is a region of the human genome containing immune system genes. Our study concerns those HLA genes that orchestrate defense against viral infections. Distinguishing HLA genes from other human genes is their extensive variation within individuals, families and populations. One advantage of this genetic variation is to increase the depth and breadth of the weaponry used against viruses; another is to impede the spread of infection within families and communities. A drawback to HLA variation is that bone-marrow transplants between donors and patients of different HLA type trigger immune reactions that attack and can kill the patient. For some patients an HLA identical family member can be the donor, but for others an unrelated HLA identical donor is sought. Facilitating these searches are registries, listing millions of possible donors whose HLA types were determined by gene sequencing. During the last ten years, this effort produced exponential growth in the number of HLA variants sequenced. This gave us the unprecedented opportunity to compare more than 10,000 sequences and distinguish aspects of the variation that are important for immune functions, from those that are not. First, however, we needed to develop software that could handle this mass of data.
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影响因子：
64.8
作者：
Kawashima, Yuka;Pfafferott, Katja;Frater, John;Matthews, Philippa;Payne, Rebecca;Addo, Marylyn;Gatanaga, Hiroyuki;Fujiwara, Mamoru;Hachiya, Atsuko;Koizumi, Hirokazu;Kuse, Nozomi;Oka, Shinichi;Duda, Anna;Prendergast, Andrew;Crawford, Hayley;Leslie, Alasdair;Brumme, Zabrina;Brumme, Chanson;Allen, Todd;Brander, Christian;Kaslow, Richard;Tang, James;Hunter, Eric;Allen, Susan;Mulenga, Joseph;Branch, Songee;Roach, Tim;John, Mina;Mallal, Simon;Ogwu, Anthony;Shapiro, Roger;Prado, Julia G.;Fidler, Sarah;Weber, Jonathan;Pybus, Oliver G.;Klenerman, Paul;Ndung'u, Thumbi;Phillips, Rodney;Heckerman, David;Harrigan, P. Richard;Walker, Bruce D.;Takiguchi, Masafumi;Goulder, Philip
通讯作者：
Goulder, Philip
影响因子：
15.3
作者：
Davis, DM;Mandelboim, O;Strominger, JL
通讯作者：
Strominger, JL
影响因子：
5.8
作者：
Larkin, M. A.;Blackshields, G.;Higgins, D. G.
通讯作者：
Higgins, D. G.
DOI：
10.1093/bioinformatics/bts199
发表时间：
2012-06-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Kearse M;Moir R;Wilson A;Stones-Havas S;Cheung M;Sturrock S;Buxton S;Cooper A;Markowitz S;Duran C;Thierer T;Ashton B;Meintjes P;Drummond A
通讯作者：
Drummond A
影响因子：
9.5
作者：
Kumar, Sudhir;Nei, Masatoshi;Tamura, Koichiro
通讯作者：
Tamura, Koichiro