scholarly journals In silico tools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual-patient and population scales

2020 ◽  
Author(s):  
Jieming Chen ◽  
Shravan Madireddi ◽  
Deepti Nagarkar ◽  
Maciej Migdal ◽  
Jason Vander Heiden ◽  
...  
Keyword(s):  
In Silico ◽  
Killer Cell ◽  
Human Leukocyte ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Leukocyte Antigen ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Kir Gene

Abstract Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of natural killer (NK) and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for four-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

scholarly journals In silico tools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual-patient and population scales

2020 ◽  
Author(s):  
Jieming Chen ◽  
Shravan Madireddi ◽  
Deepti Nagarkar ◽  
Maciej Migdal ◽  
Jason Vander Heiden ◽  
...  
Keyword(s):  
In Silico ◽  
Killer Cell ◽  
Human Leukocyte ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Leukocyte Antigen ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Kir Gene

Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of Natural Killer (NK) cells and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for 4-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

scholarly journals HLA alleles associated with asparaginase hypersensitivity in childhood ALL: a report from the DFCI Consortium

2020 ◽  
Vol 21 (8) ◽  
pp. 541-547 ◽  
Author(s):  
Vincent Gagné ◽  
Pascal St-Onge ◽  
Patrick Beaulieu ◽  
Caroline Laverdière ◽  
Jean-Marie Leclerc ◽  
...  
Keyword(s):  
Lymphoblastic Leukemia ◽  
Human Leukocyte ◽  
Sequencing Data ◽  
Treatment Protocols ◽  
Childhood All ◽  
Hla Alleles ◽  
Leukocyte Antigen ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Hla Dqa1

Aim: To evaluate the association between human leukocyte antigen (HLA) alleles and native Escherichia coli asparaginase hypersensitivity (AH) in children with acute lymphoblastic leukemia (ALL) who received Dana-Farber Cancer Institute treatment protocols. Patients & methods: HLA-DQA1, HLA-DRB1 and HLA-DQB1 alleles were retrieved from available whole exome sequencing data of a subset of childhood ALL patients from Quebec ALL cohort and analyzed for an association with AH. PCR assay was developed to analyze associated alleles in the entire discovery and replication cohorts. Results: Two alleles in linkage disequilibrium ( HLA-DRB1*07:01 and DQA1*02:01) were associated with AH. Additional analyses, performed to distinguish between HLA-DRB1*07:01 haplotypes with and without DQB1*02:02 allele, showed that the association was dependent on the presence of DQB1*02:02. Conclusion: This study confirms the implication of HLA-DRB1*07:01, DQA1*02:01 and DQB1*02:02 alleles in developing AH in childhood ALL.

scholarly journals Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity

2017 ◽  
Author(s):  
Michal Bassani-Sternberg ◽  
Chloé Chong ◽  
Philippe Guillaume ◽  
Marthe Solleder ◽  
HuiSong Pak ◽  
...  
Keyword(s):  
A Priori ◽  
Human Leukocyte ◽  
Binding Specificity ◽  
Binding Assays ◽  
Sequencing Data ◽  
Protein Structure Analysis ◽  
Binding Motifs ◽  
Leukocyte Antigen ◽  
Underlying Mechanisms

AbstractThe precise identification of Human Leukocyte Antigen class I (HLA-I) binding motifs plays a central role in our ability to understand and predict (neo-)antigen presentation in infectious diseases and cancer. Here, by exploiting co-occurrence of HLA-I alleles across ten newly generated as well as forty public HLA peptidomics datasets comprising more than 115,000 unique peptides, we show that we can rapidly and accurately identify many HLA-I binding motifs and map them to their corresponding alleles without any a priori knowledge of HLA-I binding specificity. Our approach recapitulates and refines known motifs for 43 of the most frequent alleles, uncovers new motifs for 9 alleles that up to now had less than five known ligands and provides a scalable framework to incorporate additional HLA peptidomics studies in the future. The refined motifs improve neo-antigen and cancer testis antigen predictions, indicating that unbiased HLA peptidomics data are ideal for in silico predictions of neo-antigens from tumor exome sequencing data. The new motifs further reveal allosteric modulation of the binding specificity of HLA-I alleles and we unravel the underlying mechanisms by protein structure analysis, mutagenesis and in vitro binding assays.

scholarly journals In Silico and In Vitro Analysis of Interaction between Ximelagatran and Human Leukocyte Antigen (HLA)-DRB1*07:01

2017 ◽  
Vol 18 (4) ◽  
pp. 694 ◽  
Author(s):  
Makoto Hirasawa ◽  
Katsunobu Hagihara ◽  
Koji Abe ◽  
Osamu Ando ◽  
Noriaki Hirayama
Keyword(s):  
Human Leukocyte Antigen ◽  
In Silico ◽  
Human Leukocyte ◽  
Leukocyte Antigen ◽  
Vitro Analysis ◽  
In Vitro Analysis

scholarly journals Biallelic novel mutations of the COL27A1 gene in a patient with Steel syndrome

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jong Seop Kim ◽  
Hyoungseok Jeon ◽  
Hyeran Lee ◽  
Jung Min Ko ◽  
Yonghwan Kim ◽  
...  
Keyword(s):  
Hip Dysplasia ◽  
Large Deletion ◽  
Compound Heterozygous ◽  
Radial Head Dislocation ◽  
Sequencing Data ◽  
Novel Mutations ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Carpal Coalition

AbstractAn 11-year-old Korean boy presented with short stature, hip dysplasia, radial head dislocation, carpal coalition, genu valgum, and fixed patellar dislocation and was clinically diagnosed with Steel syndrome. Scrutinizing the trio whole-exome sequencing data revealed novel compound heterozygous mutations of COL27A1 (c.[4229_4233dup]; [3718_5436del], p.[Gly1412Argfs*157];[Gly1240_Lys1812del]) in the proband, which were inherited from heterozygous parents. The maternal mutation was a large deletion encompassing exons 38–60, which was challenging to detect.

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