Comprehensive red blood cell and platelet antigen prediction from whole genome sequencing: proof of principle.
Comprehensive red blood cell and platelet antigen prediction from whole genome sequencing: proof of principle.
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DOI：
10.1111/trf.13416
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发表时间：
2016-03
期刊：
影响因子：
2.9
通讯作者：
MedSeq Project
中科院分区：
文献类型：
--
作者：
Lane WJ;Westhoff CM;Uy JM;Aguad M;Smeland-Wagman R;Kaufman RM;Rehm HL;Green RC;Silberstein LE;MedSeq Project
There are 346 serologically defined red blood cell (RBC) antigens and 33 serologically defined platelet (PLT) antigens, most of which have known genetic changes in 45 RBC or six PLT genes that correlate with antigen expression. Polymorphic sites associated with antigen expression in the primary literature and reference databases are annotated according to nucleotide positions in cDNA. This makes antigen prediction from next‐generation sequencing data challenging, since it uses genomic coordinates. The conventional cDNA reference sequences for all known RBC and PLT genes that correlate with antigen expression were aligned to the human reference genome. The alignments allowed conversion of conventional cDNA nucleotide positions to the corresponding genomic coordinates. RBC and PLT antigen prediction was then performed using the human reference genome and whole genome sequencing (WGS) data with serologic confirmation. Some major differences and alignment issues were found when attempting to convert the conventional cDNA to human reference genome sequences for the following genes: ABO, A4GALT, RHD, RHCE, FUT3, ACKR1 (previously DARC), ACHE, FUT2, CR1, GCNT2, and RHAG. However, it was possible to create usable alignments, which facilitated the prediction of all RBC and PLT antigens with a known molecular basis from WGS data. Traditional serologic typing for 18 RBC antigens were in agreement with the WGS‐based antigen predictions, providing proof of principle for this approach. Detailed mapping of conventional cDNA annotated RBC and PLT alleles can enable accurate prediction of RBC and PLT antigens from whole genomic sequencing data.
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影响因子：
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作者：
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通讯作者：
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影响因子：
20.3
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通讯作者：
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Kao CY
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影响因子：
4.4
作者：
Erlich RL;Jia X;Anderson S;Banks E;Gao X;Carrington M;Gupta N;DePristo MA;Henn MR;Lennon NJ;de Bakker PI
通讯作者：
de Bakker PI