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    Immunogenetics

    Subject:
    Genetics
    Publisher:
    Springer Berlin Heidelberg — Springer Journals
    ISSN:
    0093-7711
    Scimago Journal Rank:
    95

    2026

    Volume 78
    Issue 1 (Jul)

    2025

    Volume 78
    Issue 1 (Dec)
    Volume 77
    Issue 1 (Dec)

    2024

    Volume 77
    Issue 1 (Nov)
    Volume 76
    Issue 5-6 (Dec)Issue 4 (Aug)Issue 3 (Jun)Issue 2 (Apr)Issue 1 (Feb)

    2023

    Volume 75
    Issue 6 (Dec)Issue 5 (Oct)Issue 4 (Aug)Issue 3 (Jun)Issue 2 (Apr)Issue 1 (Feb)

    2022

    Volume 74
    Issue 6 (Dec)Issue 5 (Oct)Issue 4 (Aug)Issue 3 (Jun)Issue 2 (Apr)Issue 1 (Feb)

    2021

    Volume 73
    Issue 6 (Dec)Issue 5 (Oct)Issue 4 (Mar)Issue 3 (Jun)Issue 2 (Jan)Issue 1 (Jan)

    2020

    Volume 73
    Issue 1 (Nov)
    Volume 72
    Issue 9-10 (Nov)Issue 8 (Oct)Issue 6-7 (Aug)Issue 6 (Sep)Issue 5 (Apr)Issue 4 (May)Issue 3 (Apr)Issue 1-2 (Feb)

    2019

    Volume OnlineFirst
    December
    Volume 71
    Issue 10 (Nov)Issue 9 (Jul)Issue 8 (Sep)Issue 7 (May)Issue 6 (May)Issue 4 (Apr)Issue 3 (Jan)Issue 1 (Jan)

    2018

    Volume 71
    Issue 4 (Dec)Issue 3 (Sep)Issue 2 (Oct)Issue 1 (Oct)
    Volume 70
    Issue 10 (Jul)Issue 9 (Jun)Issue 8 (May)Issue 7 (Mar)Issue 6 (Jun)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

    2017

    Volume 70
    Issue 7 (Dec)Issue 6 (Dec)Issue 5 (Oct)Issue 4 (Sep)Issue 3 (Aug)Issue 2 (Jul)Issue 1 (Jul)
    Volume 69
    Issue 10 (Oct)Issue 9 (Jul)Issue 8-9 (Aug)Issue 7 (May)Issue 6 (Mar)Issue 5 (Feb)Issue 4 (Apr)Issue 3 (Jan)

    2016

    Volume 69
    Issue 3 (Nov)Issue 2 (Oct)Issue 1 (Sep)
    Volume 68
    Issue 10 (Aug)Issue 9 (Jun)Issue 8 (Jul)Issue 7 (May)Issue 6 (Jul)Issue 5 (Jan)Issue 4 (Jan)Issue 3 (Mar)Issue 2 (Feb)

    2015

    Volume 68
    Issue 3 (Dec)Issue 2 (Nov)Issue 1 (Sep)
    Volume 67
    Issue 12 (Oct)Issue 11 (Nov)Issue 10 (Sep)Issue 9 (Jul)Issue 8 (Jun)Issue 7 (May)Issue 6 (May)Issue 4 (Mar)Issue 3 (Jan)

    2014

    Volume 67
    Issue 3 (Dec)Issue 2 (Dec)Issue 1 (Nov)
    Volume 66
    Issue 12 (Sep)Issue 11 (Sep)Issue 10 (Jun)Issue 9 (Oct)Issue 8 (May)Issue 7 (Aug)Issue 6 (Jun)Issue 5 (Mar)Issue 4 (Jan)Issue 3 (Jan)Issue 1 (Jan)
    Volume 53
    Issue 9 (Feb)

    2013

    Volume 66
    Issue 3 (Nov)Issue 2 (Nov)Issue 1 (Oct)
    Volume 65
    Issue 12 (Oct)Issue 11 (Aug)Issue 10 (Aug)Issue 9 (Sep)Issue 8 (May)Issue 7 (Apr)Issue 6 (Mar)Issue 5 (Feb)Issue 4 (Feb)Issue 2 (Feb)

    2012

    Volume 65
    Issue 4 (Dec)Issue 3 (Dec)Issue 2 (Nov)Issue 1 (Oct)
    Volume 64
    Issue 12 (Sep)Issue 11 (Aug)Issue 10 (Jul)Issue 9 (Sep)Issue 8 (May)Issue 7 (Jul)Issue 6 (Feb)Issue 5 (Feb)Issue 3 (Jan)Issue 2 (Feb)

    2011

    Volume 64
    Issue 5 (Dec)Issue 4 (Nov)Issue 3 (Sep)Issue 2 (Dec)Issue 1 (Jul)
    Volume 63
    Issue 12 (Dec)Issue 11 (Jun)Issue 10 (Jun)Issue 9 (Jun)Issue 8 (May)Issue 7 (Mar)Issue 6 (Jun)Issue 5 (Feb)Issue 4 (Jan)Issue 3 (Jan)

    2010

    Volume 63
    Issue 4 (Dec)Issue 3 (Dec)Issue 2 (Oct)Issue 1 (Nov)
    Volume 62
    Issue 12 (Sep)Issue 10 (Aug)Issue 9 (Jul)Issue 8 (May)Issue 7 (May)Issue 6 (Apr)Issue 5 (Mar)Issue 4 (Mar)Issue 3 (Feb)Issue 2 (Jan)Issue 1 (Jan)
    Volume 61
    Issue 12 (Jan)

    2009

    Volume 62
    Issue 2 (Dec)Issue 1 (Nov)
    Volume 61
    Issue 12 (Nov)Issue 10 (Sep)Issue 9 (Sep)Issue 8 (Aug)Issue 7 (Jun)Issue 6 (May)Issue 5 (May)Issue 4 (Feb)Issue 3 (Feb)Issue 2 (Jan)

    2008

    Volume 61
    Issue 3 (Dec)Issue 2 (Dec)Issue 1 (Nov)
    Volume 60
    Issue 12 (Oct)Issue 11 (Aug)Issue 10 (Oct)Issue 9 (Jul)Issue 8 (Jun)Issue 7 (Jul)Issue 6 (May)Issue 5 (Apr)Issue 4 (Mar)Issue 2 (Feb)Issue 1 (Jan)

    2007

    Volume 60
    Issue 1 (Dec)
    Volume 59
    Issue 12 (Nov)Issue 11 (Oct)Issue 10 (Sep)Issue 9 (Aug)Issue 8 (Aug)Issue 7 (May)Issue 6 (Apr)Issue 5 (Feb)Issue 4 (Feb)Issue 3 (Mar)Issue 2 (Feb)
    Volume 44
    Issue 6 (Apr)Issue 5 (Apr)Issue 4 (Apr)Issue 3 (Apr)Issue 2 (Jun)Issue 1 (Apr)

    2006

    Volume 59
    Issue 2 (Dec)Issue 1 (Nov)
    Volume 58
    Issue 12 (Dec)Issue 11 (Oct)Issue 10 (Oct)Issue 9 (Aug)Issue 8 (Jun)Issue 7 (Jul)Issue 6 (Apr)Issue 5 (Jun)Issue 4 (May)Issue 3 (Mar)Issue 1 (Feb)
    Volume 57
    Issue 12 (Jan)
    Volume 43
    Issue 5 (Jun)
    Volume 30
    Issue 6 (Apr)Issue 5 (May)Issue 4 (Apr)Issue 3 (Apr)Issue 2 (Apr)Issue 1 (Apr)
    Volume 29
    Issue 1 (Feb)

    2005

    Volume 57
    Issue 12 (Dec)Issue 11 (Dec)Issue 10 (Nov)Issue 9 (Sep)Issue 8 (Aug)Issue 7 (Jul)Issue 6 (Jul)Issue 5 (May)Issue 4 (Apr)Issue 3 (May)Issue 2 (Mar)Issue 1 (Apr)
    Volume 56
    Issue 12 (Jan)Issue 11 (Feb)Issue 10 (Jan)
    Volume 43
    Issue 6 (Sep)
    Volume 40
    Issue 5 (Feb)
    Volume 34
    Issue 6 (May)
    Volume 33
    Issue 3 (May)
    Volume 32
    Issue 3 (Aug)Issue 1 (May)
    Volume 31
    Issue 6 (Aug)
    Volume 12
    Issue 1 (Apr)
    Volume 11
    Issue 1 (Apr)
    Volume 10
    Issue 5 (Apr)Issue 4 (Apr)
    Volume 9
    Issue 1 (Apr)
    Volume 8
    Issue 1 (Apr)
    Volume 7
    Issue 1 (May)
    Volume 6
    Issue 1 (Apr)
    Volume 5
    Issue 1 (Apr)
    Volume 4
    Issue 1 (Apr)
    Volume 3
    Issue 1 (Apr)
    Volume 2
    Issue 1 (Apr)
    Volume 1
    Issue 1 (Apr)

    2004

    Volume 56
    Issue 12 (Dec)Issue 11 (Dec)Issue 10 (Dec)Issue 9 (Nov)Issue 8 (Oct)Issue 7 (Sep)Issue 6 (Sep)Issue 5 (Aug)Issue 4 (Jun)Issue 3 (May)Issue 2 (Apr)Issue 1 (Mar)
    Volume 55
    Issue 12 (Feb)Issue 11 (Jan)Issue 10 (Jan)
    Volume 43
    Issue 4 (Jun)Issue 3 (Jul)Issue 2 (Jul)
    Volume 42
    Issue 6 (Jul)Issue 5 (Jul)Issue 4 (Jul)Issue 3 (Jul)Issue 2 (Jul)Issue 1 (Jun)
    Volume 41
    Issue 6 (Jun)Issue 5 (Jul)Issue 4 (Jul)Issue 3 (Jul)Issue 1 (Jul)
    Volume 40
    Issue 6 (Jul)Issue 4 (Jul)Issue 3 (Jun)Issue 2 (Jul)Issue 1 (Jun)
    Volume 39
    Issue 6 (Jul)Issue 5 (Jul)Issue 4 (Jul)Issue 3 (Jul)Issue 2 (Jul)Issue 1 (Jul)
    Volume 38
    Issue 6 (Jul)Issue 5 (Jul)Issue 4 (Jul)Issue 3 (Jul)Issue 2 (Jul)Issue 1 (Jul)
    Volume 37
    Issue 6 (Jul)Issue 5 (Jul)Issue 4 (Jul)Issue 3 (Jul)Issue 2 (Jul)Issue 1 (Jul)
    Volume 36
    Issue 6 (Jul)Issue 5 (Jul)Issue 4 (Jul)Issue 3 (Nov)Issue 2 (Jul)Issue 1 (Jul)
    Volume 35
    Issue 6 (Jul)Issue 5 (Jul)Issue 4 (Jun)Issue 3 (Jul)Issue 2 (Jul)Issue 1 (Jul)
    Volume 34
    Issue 5 (Jul)Issue 4 (Jul)Issue 3 (Jul)Issue 2 (Jul)Issue 1 (Jul)
    Volume 33
    Issue 6 (Jul)Issue 4 (Jul)Issue 2 (Jul)Issue 1 (Jul)
    Volume 32
    Issue 6 (Jul)Issue 5 (Jul)Issue 4 (Jul)Issue 2 (Jul)
    Volume 31
    Issue 4 (Jul)Issue 3 (Jul)Issue 2 (Nov)Issue 1 (Nov)
    Volume 29
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Nov)Issue 3 (Sep)Issue 2 (Sep)
    Volume 28
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 27
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 26
    Issue 6 (Sep)Issue 5 (Sep)Issue 3 (Sep)Issue 2 (Sep)
    Volume 25
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 24
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 23
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 22
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Oct)Issue 1 (Sep)
    Volume 21
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 20
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 19
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 18
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 17
    Issue 6 (Sep)Issue 5 (Nov)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 16
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 15
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Sep)Issue 1 (Sep)
    Volume 14
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 2 (Sep)
    Volume 13
    Issue 6 (Sep)Issue 5 (Sep)Issue 4 (Sep)Issue 3 (Sep)Issue 2 (Oct)

    2003

    Volume 55
    Issue 10 (Dec)Issue 9 (Nov)Issue 8 (Oct)Issue 7 (Aug)Issue 6 (Aug)Issue 5 (Aug)Issue 4 (Jun)Issue 3 (Jun)Issue 2 (Apr)Issue 1 (Mar)
    Volume 54
    Issue 12 (Feb)Issue 11 (Feb)Issue 10 (Jan)

    2002

    Volume 54
    Issue 10 (Dec)Issue 9 (Dec)Issue 8 (Nov)Issue 7 (Oct)Issue 6 (Sep)Issue 5 (Aug)Issue 4 (Jul)Issue 3 (Jun)Issue 2 (May)Issue 1 (Apr)
    Volume 53
    Issue 12 (Feb)Issue 11 (Feb)Issue 10 (Feb)

    2001

    Volume 53
    Issue 9 (Dec)Issue 8 (Oct)Issue 7 (Sep)Issue 6 (Aug)Issue 5 (Jul)Issue 4 (May)Issue 3 (Apr)Issue 2 (Mar)Issue 1 (Feb)
    Volume 52
    Issue 4 (Jan)

    2000

    Volume 52
    Issue 2 (Nov)Issue 1 (Nov)
    Volume 51
    Issue 12 (Oct)Issue 11 (Sep)Issue 10 (Aug)Issue 9 (Jul)Issue 7 (Jun)Issue 6 (May)Issue 5 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

    1999

    Volume 50
    Issue 6 (Dec)Issue 4 (Nov)Issue 3 (Nov)Issue 2 (Oct)Issue 1 (Oct)
    Volume 49
    Issue 12 (Sep)Issue 11-12 (Sep)Issue 10 (Aug)Issue 9 (Jul)Issue 8 (Jun)Issue 7-8 (Jun)Issue 6 (May)Issue 5 (Apr)Issue 4 (Mar)Issue 3 (Jan)Issue 2 (Feb)Issue 1 (Jan)

    1998

    Volume 48
    Issue 6 (Oct)Issue 5 (Sep)Issue 4 (Aug)Issue 3 (Jul)Issue 2 (Jun)Issue 1 (May)
    Volume 47
    Issue 6 (Apr)Issue 5 (Mar)Issue 4 (Feb)Issue 3 (Jan)

    1997

    Volume 47
    Issue 2 (Dec)Issue 1 (Nov)
    Volume 46
    Issue 6 (Oct)Issue 5 (Sep)Issue 4 (Jul)Issue 3 (Jul)Issue 2 (Jun)Issue 1 (May)
    Volume 45
    Issue 6 (Apr)Issue 5 (Mar)Issue 4 (Jan)Issue 3 (Jan)

    1996

    Volume 45
    Issue 2 (Dec)Issue 1 (Nov)
    Volume 44
    Issue 6 (Oct)Issue 5 (Sep)Issue 4 (Aug)Issue 3 (May)Issue 2 (Mar)Issue 1 (Apr)
    Volume 43
    Issue 6 (Nov)Issue 5 (Mar)

    1995

    Volume 42
    Issue 5 (Sep)
    Volume 41
    Issue 5 (Mar)Issue 4 (Feb)

    1994

    Volume 39
    Issue 2 (Jan)

    1993

    Volume 38
    Issue 4 (Jun)

    1992

    Volume 36
    Issue 5 (Aug)
    Volume 35
    Issue 3 (Feb)

    1990

    Volume 32
    Issue 1 (Jan)

    1989

    Volume 30
    Issue 6 (Dec)Issue 1 (Jul)
    Volume 29
    Issue 3 (Mar)

    1987

    Volume 26
    Issue 4-5 (Jul)Issue 4 (Jul)

    1986

    Volume 24
    Issue 6 (Dec)Issue 1 (Jul)
    Volume 23
    Issue 6 (Jun)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

    1985

    Volume 22
    Issue 6 (Dec)
    Volume 21
    Issue 6 (Jun)Issue 5 (May)Issue 3 (Mar)Issue 2 (Feb)

    1984

    Volume 20
    Issue 6 (Dec)Issue 4 (Oct)Issue 3 (Sep)Issue 2 (Aug)Issue 1 (Jul)
    Volume 19
    Issue 5 (May)Issue 1 (Jan)

    1983

    Volume 18
    Issue 6 (Dec)Issue 4 (Oct)Issue 3 (May)
    Volume 17
    Issue 5 (Sep)Issue 1 (Jan)

    1982

    Volume 16
    Issue 6 (Dec)Issue 3 (Sep)
    Volume 15
    Issue 1 (Jan)

    1981

    Volume 14
    Issue 3-4 (Oct)Issue 3 (Oct)
    Volume 13
    Issue 6 (Aug)Issue 3 (May)
    Volume 12
    Issue 1 (Dec)

    1980

    Volume 11
    Issue 1 (Dec)
    Volume 10
    Issue 5 (Oct)Issue 1-4 (Feb)

    1979

    Volume 9
    Issue 1 (Dec)
    Volume 8
    Issue 1 (Dec)

    1978

    Volume 7
    Issue 1 (Dec)
    Volume 6
    Issue 1 (Dec)

    1977

    Volume 5
    Issue 1 (Dec)
    Volume 4
    Issue 1 (Dec)

    1976

    Volume 3
    Issue 1 (Dec)

    1975

    Volume 2
    Issue 1 (Dec)

    1974

    Volume 1
    Issue 1 (Dec)
    journal article
    LitStream Collection
    Fractal genomics of SOD1 evolution

    Saeed, Mohammad

    2020 Immunogenetics

    doi: 10.1007/s00251-020-01184-4pmid: 33237378

    To understand the fundamental processes of gene evolution such as the impact of point mutations and segmental duplications on statistical topography, superoxide dismutase-1 (SOD1) orthologous sequences (n = 50) are studied. These demonstrate scale invariant self-similarity patterns and long-range correlations (LRCs) indicating fractal organization. Phylogenetic hierarchies change when SOD1 orthologs are grouped according to fractal measures, indicating that statistical topographies can be used to study gene evolution. Sliding window k-mer analysis show that majority of k-mers across all SOD1 orthologs are unique, with very few duplications. Orthologs from simpler species contribute minimally (< 1% of k-mers) to more complex species. Both simple and complex random processes fail to produce significant matching k-mer sequences for SOD1 orthologs. Point mutations causing amyotrophic lateral sclerosis do not impact the fractal organization of human SOD1. Hence, SOD1 did not evolve by a patchwork of repetitive sequences modified by point mutations. Moreover, fractal and other methods described here can be used to study the origin and evolution of genomes.
    journal article
    LitStream Collection
    Ethnic variation in risk genotypes based on single nucleotide polymorphisms (SNPs) of the interferon-inducible transmembrane 3 (IFITM3) gene, a susceptibility factor for pandemic 2009 H1N1 influenza A virus

    Kim, Yong-Chan; Jeong, Byung-Hoon

    2020 Immunogenetics

    doi: 10.1007/s00251-020-01188-0pmid: 33174121

    The interferon-inducible transmembrane 3 (IFITM3) protein is an effector of the host innate immune system that shows defensive activity against a wide range of viruses, including the influenza A virus. Previous studies have reported that three transcription-related regulatory single nucleotide polymorphisms (SNPs), rs12252, rs34481144, and rs6598045, showed potent associations with the severity of pandemic influenza A 2009 infection and susceptibility to this virus, respectively. However, the distribution of the risk genotypes of these three SNPs according to ethnic background has remained elusive. In this study, we compared the genotype and allele frequencies of the IFITM3 polymorphisms among several ethnic groups including American, African, European, South Asian, and East Asian using chi-square test. In addition, we analyzed the worldwide distribution of risk genotypes for pandemic influenza A 2009 virus infection. We found that the genotype and allele distributions of the rs12252, rs34481144, and rs6598045 SNPs were significantly different among several ethnic groups. In addition, the risk genotypes of the IFITM3 polymorphisms were also significantly different worldwide. To the best of our knowledge, this was the first simultaneous estimation of the risk genotypes of the IFITM3 gene with respect to pandemic influenza A 2009 virus infection.
    journal article
    LitStream Collection
    Identification of immune-related gene signature predicting survival in the tumor microenvironment of lung adenocarcinoma

    Zhao, Mengnan; Li, Ming; Chen, Zhencong; Bian, Yunyi; Zheng, Yuansheng; Hu, Zhengyang; Liang, Jiaqi; Huang, Yiwei; Yin, Jiacheng; Zhan, Cheng; Feng, Mingxiang; Wang, Qun

    2020 Immunogenetics

    doi: 10.1007/s00251-020-01189-z

    journal article
    LitStream Collection
    Replication study and meta-analysis indicate a suggestive association of RUNX3 locus with primary biliary cholangitis

    Jawed, Rohil; Zhang, Mingming; Wang, Chan; Yang, Shu-Han; Jiang, Peng; Wu, Qiuyuan; Li, Li; Chen, Weichang; Gershwin, M. Eric; Tian, Ye; Seldin, Michael F.; Ma, Xiong; Liu, Xiangdong; Lian, Zhe-Xiong; Shi, Xingjuan

    2020
    journal article
    Open Access Collection
    Evolution of HLA-F and its orthologues in primate species: a complex tale of conservation, diversification and inactivation

    Otting, N.; de Groot, N. G.; Bontrop, R. E.

    2020 Immunogenetics

    doi: 10.1007/s00251-020-01187-1pmid: 33184728

    HLA-F represents one of the nonclassical MHC class I molecules in humans. Its main characteristics involve low levels of polymorphism in combination with a restricted tissue distribution. This signals that the gene product executes a specialised function, which, however, is still poorly understood. Relatively little is known about the evolutionary equivalents of this gene in nonhuman primates, especially with regard to population data. Here we report a comparative genetic analysis of the orthologous genes of HLA-F in various great ape, Old World monkey (OWM), and New World monkey (NWM) species. HLA-F-related transcripts were found in all subjects studied. Low levels of polymorphism were encountered, although the length of the predicted gene products may vary. In most species, one or two transcripts were discovered, indicating the presence of only one active F-like gene per chromosome. An exception was provided by a New World monkey species, namely, the common marmoset. In this species, the gene has been subject to duplication, giving rise to up to six F-like transcripts per animal. In humans, great apes, and OWM, and probably the majority of the NWM species, the evolutionary equivalents of the HLA-F gene experienced purifying selection. In the marmoset, however, the gene was initially duplicated, but the expansion was subjected afterwards to various mechanisms of genetic inactivation, as evidenced by the presence of pseudogenes and an array of genetic artefacts in a section of the transcripts.
    journal article
    LitStream Collection
    Association of HLA-DQ and IL13 gene variants with challenge-proven shrimp allergy in West Bengal, India

    Laha, Arghya; Ghosh, Amlan; Moitra, Saibal; Biswas, Himani; Saha, Nimai Chandra; Bhattacharya, Srijit; Saha, Goutam Kumar; Podder, Sanjoy

    2020 Immunogenetics

    doi: 10.1007/s00251-020-01185-3pmid: 33175217

    Little is known about genetic factors and mechanisms underlying shrimp allergy. Genome-wide association studies identified HLA class-II and IL13 genes as highly plausible candidates for shrimp allergy. The present study was designed to investigate potential associations of HLA-DQ rs9275596, IL13 rs20541, and IL13 rs1800925 polymorphisms with challenge-proven shrimp allergy using the data from 532 people of West Bengal, India; selected on basis of positive skin prick test, elevated specific IgE and medical history. Risk genotypes, i.e., HLA-DQ rs9275596 CC, IL13 rs20541 AA, and IL13 rs1800925 TT, were found to be significantly associated with challenge positive shrimp allergy (P = 0.04, 0.01, and 0.03, respectively). Distribution of genotypes for HLA-DQ and IL13 polymorphisms in allergic and control subjects showed significant difference between younger (20–40 years) and older (> 40 years) age group (P = 0.006). Risk genotypes significantly associated with elevated shrimp-specific IgE. IL13 TA haplotype significantly associated with shrimp allergy and elevated specific IgE (P = 0.02). Synergistic effect of IL13 TA haplotype–HLA-DQ rs9275596 CC genotype interaction significantly elevated specific IgE (P = 0.03). The present study suggests that HLA-DQ and IL13 polymorphisms pose major risk for shrimp allergic patients in West Bengal, India and thus could be helpful for early target-specific therapeutic intervention in near future.
    journal article
    Open Access Collection
    High-throughput immunogenetic typing of koalas suggests possible link between MHC alleles and cancers

    Quigley, Bonnie L.; Tzipori, Galit; Nilsson, Karen; Timms, Peter

    2020 Immunogenetics

    doi: 10.1007/s00251-020-01181-7pmid: 33083849

    Characterizing the allelic diversity within major histocompatibility complex (MHC) genes is an important way of determining the potential genetic resilience of a population to infectious and ecological pressures. For the koala (Phascolarctos cinereus), endemic diseases, anthropogenic factors and climate change are all placing increased pressure on this vulnerable marsupial. To increase the ability of researchers to study MHC genetics in koalas, this study developed and tested a high-throughput immunogenetic profiling methodology for targeting MHC class I UA and UC genes and MHC class II DAB, DBB, DCB and DMB genes in a population of 82 captive koalas. This approach was validated by comparing the determined allelic profiles from 36 koala family units (18 dam-sire-joey units and 18 parent-joey pairs), finding 96% overall congruence within family profiles. Cancers are a significant cause of morbidity in koalas and the risk factors remain undetermined. Our analysis of this captive population revealed several novel MHC alleles, including a potential link between the DBB*03 allele and a risk of developing cancer. This method offers a reliable, high-throughput protocol for expanded study into koala immunogenetics.
    journal article
    LitStream Collection
    Evidence for the loss of plasminogen receptor KT gene in chicken

    Sharma, Sandhya; Shinde, Sagar Sharad; Teekas, Lokdeep; Vijay, Nagarjun

    2020 Immunogenetics

    doi: 10.1007/s00251-020-01186-2pmid: 33247773

    The loss of conserved genes has the potential to alter phenotypes drastically. Screening of vertebrate genomes for lineage-specific gene loss events has identified numerous natural knockouts associated with specific phenotypes. We provide evidence for the loss of a multi-exonic plasminogen receptor KT (PLGRKT) protein-encoding gene located on the Z chromosome in chicken. Exons 1 and 2 are entirely missing; remnants of exon 3 and a mostly intact exon 4 are identified in an assembly gap-free region in chicken with conserved synteny across species and verified using transcriptome and genome sequencing. PLGRKT gene disrupting changes are present in representative species from all five galliform families. In contrast to this, the presence of an intact transcriptionally active PLGRKT gene in species such as mallard, swan goose, and Anolis lizard suggests that gene loss occurred in the galliform lineage sometime between 68 and 80 Mya. The presence of galliform specific chicken repeat 1 (CR1) insertion at the erstwhile exon 2 of PLGRKT gene suggests repeat insertion-mediated loss. However, at least nine other independent PLGRKT coding frame disrupting changes in other bird species are supported by genome sequencing and indicate a role for relaxed purifying selection before CR1 insertion. The recurrent loss of a conserved gene with a role in the regulation of macrophage migration, efferocytosis, and blood coagulation is intriguing. Hence, we propose potential candidate genes that might be compensating the function of PLGRKT based on the presence of a C-terminal lysine residue, transmembrane domains, and gene expression patterns.

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    Nature GeneticsNucleic Acids ResearchGeneticsAnnual Review of GeneticsGenomicsMammalian GenomeChromosome ResearchJournal of GeneticsRussian Journal of Genetics
    pmid:
    33188484
    The tumor microenvironment (TME) plays an essential role in the occurrence and progression of malignancy. The potential prognostic TME-related biomarkers of lung adenocarcinoma (LUAD) remained unclear, which were investigated in this research. The RNA-sequencing profiles and corresponding clinical parameters were extracted from TCGA and GEO databases, based on which the stromal and immune scores were calculated through the ESTIMATE algorithm. Overlapping differentially expressed genes between stromal and immune score group were analyzed by the LASSO and Random Forrest algorithms and validated in cases from our center. And a prognostic 8-gene signature was constructed using Cox regression. The infiltration of 22 hematopoietic cell phenotypes was assessed by the CIBERSORT algorithms. We found that female, elder patients, and solid predominant subtype had obviously higher stromal and immune scores. And patients with early stage LUAD received a prominently higher immune score. A high stromal or immune score meant a good prognosis. Subsequently, eight TME-related prognostic genes (ATAD5, CYP4F3, CYP4F12, ESPNL, FXYD2, GPX2, NLGN4Y, and SERPINC1) were identified by both LASSO regression and Radom Forest algorithms. High 8-gene signature group exhibited worse overall survival. Furthermore, B cell naïve, plasma cells, T cell follicular helper, and macrophages M1 were prominently more in high signature group. Nevertheless, fewer T cells CD4 memory resting, monocytes, and dendritic cell resting were identified in the high signature group. The composition of the tumor microenvironment significantly affected the prognosis of LUAD patients. We provided a new strategy for the exploration of prognostic TME-related biomarkers and immunotherapy.
    Immunogenetics

    doi: 10.1007/s00251-020-01192-4pmid: 33284381

    Susceptibility to primary biliary cholangitis (PBC) is in part genetically determined. In our previous PBC genome-wide association study (GWAS) in 1118 Han Chinese PBC and 4036 controls, we noted that multiple SNPs in the runt-related transcription factor 3 (RUNX3) regions showed a nominally significant association. The tag SNP rs7529070 was genotyped using a TaqMan assay in a separately collected 1435 PBC and 3205 controls. A meta-analysis with a combined 2553 PBC and 7241 controls showed that rs7529070 is still nominally associated with PBC (p = 1.7 × 10–4, odds ratio (OR) = 1.18, 95% confidence interval (CI) = 1.08–1.28). Further analysis indicated that the risk allele of rs7529070 (G allele) is in complete linkage disequilibrium (LD) (r2 = 1) with the G allele of rs4648889, which is known to be associated with increased RUNX3 expression. Bioinformatic analysis with existing expression data showed that the expression of RUNX3 is significantly increased in PBC patients (p = 0.001) and the expression level is correlated with disease severity. Consistently, we also found significantly increased RUNX3 expression (p < 0.01) in the livers of dnTGFβRII mice (a PBC mouse model). This study suggests that the RUNX3 locus may associate with PBC in Han Chinese.