A new HLA‐A*31 null allele, A*3114N†

Smith, Douglas M.; Gardner, W.B.; Baker, Judy; Cox, S.T.; Kresie, Lesley

doi:10.1111/j.1399-0039.2006.00700.x

Cited by 6 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The insertion occurred in a homopolymeric region at the beginning of exon 4 of the HLA-A gene, which changed the HLA-A allele from A*31:01:02 to A*31:14N. This region is known as an insertion hotspot in some HLA types such as A*01:04N and B*51:11N, and the insertion causes no expression of the allele [23][24][25][26]. The three indels identified were validated by the TruSight HLA Sequencing Panels and the Sanger sequencing.…”

Section: Detection Of Somatic Mutationsmentioning

confidence: 99%

ALPHLARD: a Bayesian method for analyzing HLA genes from whole genome sequence data

Hayashi

Yamaguchi

Mizuno

et al. 2018

Preprint

View full text Add to dashboard Cite

Although human leukocyte antigen (HLA) genotyping based on amplicon, whole exome sequence (WES), and RNA sequence data has been achieved in recent years, accurate genotyping from whole genome sequence (WGS) data remains a challenge due to the low depth. Furthermore, there is no method to identify the sequences of unknown HLA types not registered in HLA databases. We developed a Bayesian model, called ALPHLARD, that collects reads potentially generated from HLA genes and accurately determines a pair of HLA types for each of HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, and -DRB1 genes at 6-digit resolution. Furthermore, ALPHLARD can detect rare germline variants not stored in HLA databases and call somatic mutations from paired normal and tumor sequence data. We illustrate the capability of ALPHLARD using 253 WES data and 25 WGS data from Illumina platforms. By comparing the results of HLA genotyping from SBT and amplicon sequencing methods, ALPHLARD achieved 98.8% for WES data and 98.5% for WGS data at 4-digit resolution. We also detected three somatic point mutations and one case of loss of heterozygosity in the HLA genes from the WGS data. ALPHLARD showed good performance for HLA genotyping even from low-coverage data. It also has a potential to detect rare germline variants and somatic mutations in HLA genes. It would help to fill in the current gaps in HLA reference databases and unveil the immunological significance of somatic mutations identified in HLA genes.

show abstract

Section: Detection Of Somatic Mutationsmentioning

confidence: 99%

ALPHLARD: a Bayesian method for analyzing HLA genes from whole genome sequence data

Hayashi

Yamaguchi

Mizuno

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…A*1118 (Voorter et al, 2006) A*240208 (Tang et al, 2006) A*2630 (Gill et al, 2006) A*2915 (Gill et al, 2006) A*3114N (Smith et al, 2006) A*3211Q (Tang et al, 2006) A*680105 (Gill et al, 2006) A*9202 (Gill et al, 2006 (Tang et al, 2006) Cw*0321 (Tang et al, 2006) Cw*0734 (Tang et al, 2006) Cw*0742 (Balas et al, 2006) DRB1*1155 (Witter et al, 2006b) DRB3*020205 (Curcio et al, 2006)…”

Section: Sequence Referencesmentioning

confidence: 99%