Functional Genetics to Understand the Etiology of Autoimmunity

Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Hiroaki Hatano [verfasserIn] Kazuyoshi Ishigaki [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	V2F immunogenetics TCR eQTL sQTL

Übergeordnetes Werk:	In: Genes - MDPI AG, 2010, 14(2023), 3, p 572
Übergeordnetes Werk:	volume:14 ; year:2023 ; number:3, p 572

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/genes14030572

Katalog-ID:	DOAJ087359197

Internformat


LEADER	01000caa a22002652 4500
001	DOAJ087359197
003	DE-627
005	20240413051450.0
007	cr uuu---uuuuu
008	230331s2023 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.3390/genes14030572 \|2 doi
035			\|a (DE-627)DOAJ087359197
035			\|a (DE-599)DOAJ6844f53851054c6b8cdc54785aac56d1
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
050		0	\|a QH426-470
100	0		\|a Hiroaki Hatano \|e verfasserin \|4 aut
245	1	0	\|a Functional Genetics to Understand the Etiology of Autoimmunity
264		1	\|c 2023
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
520			\|a Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review.
650		4	\|a V2F
650		4	\|a immunogenetics
650		4	\|a TCR
650		4	\|a eQTL
650		4	\|a sQTL
653		0	\|a Genetics
700	0		\|a Kazuyoshi Ishigaki \|e verfasserin \|4 aut
773	0	8	\|i In \|t Genes \|d MDPI AG, 2010 \|g 14(2023), 3, p 572 \|w (DE-627)614096537 \|w (DE-600)2527218-4 \|x 20734425 \|7 nnns
773	1	8	\|g volume:14 \|g year:2023 \|g number:3, p 572
856	4	0	\|u https://doi.org/10.3390/genes14030572 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/6844f53851054c6b8cdc54785aac56d1 \|z kostenfrei
856	4	0	\|u https://www.mdpi.com/2073-4425/14/3/572 \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/2073-4425 \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_95
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_213
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4700
951			\|a AR
952			\|d 14 \|j 2023 \|e 3, p 572

Indexfelder

author_variant	h h hh k i ki
matchkey_str	article:20734425:2023----::ucinleeisonesadheil
hierarchy_sort_str	2023
callnumber-subject-code	QH
publishDate	2023
allfields	10.3390/genes14030572 doi (DE-627)DOAJ087359197 (DE-599)DOAJ6844f53851054c6b8cdc54785aac56d1 DE-627 ger DE-627 rakwb eng QH426-470 Hiroaki Hatano verfasserin aut Functional Genetics to Understand the Etiology of Autoimmunity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review. V2F immunogenetics TCR eQTL sQTL Genetics Kazuyoshi Ishigaki verfasserin aut In Genes MDPI AG, 2010 14(2023), 3, p 572 (DE-627)614096537 (DE-600)2527218-4 20734425 nnns volume:14 year:2023 number:3, p 572 https://doi.org/10.3390/genes14030572 kostenfrei https://doaj.org/article/6844f53851054c6b8cdc54785aac56d1 kostenfrei https://www.mdpi.com/2073-4425/14/3/572 kostenfrei https://doaj.org/toc/2073-4425 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 3, p 572
spelling	10.3390/genes14030572 doi (DE-627)DOAJ087359197 (DE-599)DOAJ6844f53851054c6b8cdc54785aac56d1 DE-627 ger DE-627 rakwb eng QH426-470 Hiroaki Hatano verfasserin aut Functional Genetics to Understand the Etiology of Autoimmunity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review. V2F immunogenetics TCR eQTL sQTL Genetics Kazuyoshi Ishigaki verfasserin aut In Genes MDPI AG, 2010 14(2023), 3, p 572 (DE-627)614096537 (DE-600)2527218-4 20734425 nnns volume:14 year:2023 number:3, p 572 https://doi.org/10.3390/genes14030572 kostenfrei https://doaj.org/article/6844f53851054c6b8cdc54785aac56d1 kostenfrei https://www.mdpi.com/2073-4425/14/3/572 kostenfrei https://doaj.org/toc/2073-4425 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 3, p 572
allfields_unstemmed	10.3390/genes14030572 doi (DE-627)DOAJ087359197 (DE-599)DOAJ6844f53851054c6b8cdc54785aac56d1 DE-627 ger DE-627 rakwb eng QH426-470 Hiroaki Hatano verfasserin aut Functional Genetics to Understand the Etiology of Autoimmunity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review. V2F immunogenetics TCR eQTL sQTL Genetics Kazuyoshi Ishigaki verfasserin aut In Genes MDPI AG, 2010 14(2023), 3, p 572 (DE-627)614096537 (DE-600)2527218-4 20734425 nnns volume:14 year:2023 number:3, p 572 https://doi.org/10.3390/genes14030572 kostenfrei https://doaj.org/article/6844f53851054c6b8cdc54785aac56d1 kostenfrei https://www.mdpi.com/2073-4425/14/3/572 kostenfrei https://doaj.org/toc/2073-4425 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 3, p 572
allfieldsGer	10.3390/genes14030572 doi (DE-627)DOAJ087359197 (DE-599)DOAJ6844f53851054c6b8cdc54785aac56d1 DE-627 ger DE-627 rakwb eng QH426-470 Hiroaki Hatano verfasserin aut Functional Genetics to Understand the Etiology of Autoimmunity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review. V2F immunogenetics TCR eQTL sQTL Genetics Kazuyoshi Ishigaki verfasserin aut In Genes MDPI AG, 2010 14(2023), 3, p 572 (DE-627)614096537 (DE-600)2527218-4 20734425 nnns volume:14 year:2023 number:3, p 572 https://doi.org/10.3390/genes14030572 kostenfrei https://doaj.org/article/6844f53851054c6b8cdc54785aac56d1 kostenfrei https://www.mdpi.com/2073-4425/14/3/572 kostenfrei https://doaj.org/toc/2073-4425 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 3, p 572
allfieldsSound	10.3390/genes14030572 doi (DE-627)DOAJ087359197 (DE-599)DOAJ6844f53851054c6b8cdc54785aac56d1 DE-627 ger DE-627 rakwb eng QH426-470 Hiroaki Hatano verfasserin aut Functional Genetics to Understand the Etiology of Autoimmunity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review. V2F immunogenetics TCR eQTL sQTL Genetics Kazuyoshi Ishigaki verfasserin aut In Genes MDPI AG, 2010 14(2023), 3, p 572 (DE-627)614096537 (DE-600)2527218-4 20734425 nnns volume:14 year:2023 number:3, p 572 https://doi.org/10.3390/genes14030572 kostenfrei https://doaj.org/article/6844f53851054c6b8cdc54785aac56d1 kostenfrei https://www.mdpi.com/2073-4425/14/3/572 kostenfrei https://doaj.org/toc/2073-4425 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 3, p 572
language	English
source	In Genes 14(2023), 3, p 572 volume:14 year:2023 number:3, p 572
sourceStr	In Genes 14(2023), 3, p 572 volume:14 year:2023 number:3, p 572
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	V2F immunogenetics TCR eQTL sQTL Genetics
isfreeaccess_bool	true
container_title	Genes
authorswithroles_txt_mv	Hiroaki Hatano @@aut@@ Kazuyoshi Ishigaki @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	614096537
id	DOAJ087359197
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ087359197</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240413051450.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230331s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/genes14030572</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ087359197</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ6844f53851054c6b8cdc54785aac56d1</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QH426-470</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Hiroaki Hatano</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Functional Genetics to Understand the Etiology of Autoimmunity</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">V2F</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">immunogenetics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">TCR</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">eQTL</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">sQTL</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Genetics</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Kazuyoshi Ishigaki</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Genes</subfield><subfield code="d">MDPI AG, 2010</subfield><subfield code="g">14(2023), 3, p 572</subfield><subfield code="w">(DE-627)614096537</subfield><subfield code="w">(DE-600)2527218-4</subfield><subfield code="x">20734425</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:14</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:3, p 572</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/genes14030572</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/6844f53851054c6b8cdc54785aac56d1</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/2073-4425/14/3/572</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2073-4425</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">14</subfield><subfield code="j">2023</subfield><subfield code="e">3, p 572</subfield></datafield></record></collection>
callnumber-first	Q - Science
author	Hiroaki Hatano
spellingShingle	Hiroaki Hatano misc QH426-470 misc V2F misc immunogenetics misc TCR misc eQTL misc sQTL misc Genetics Functional Genetics to Understand the Etiology of Autoimmunity
authorStr	Hiroaki Hatano
ppnlink_with_tag_str_mv	@@773@@(DE-627)614096537
format	electronic Article
delete_txt_mv	keep
author_role	aut aut
collection	DOAJ
remote_str	true
callnumber-label	QH426-470
illustrated	Not Illustrated
issn	20734425
topic_title	QH426-470 Functional Genetics to Understand the Etiology of Autoimmunity V2F immunogenetics TCR eQTL sQTL
topic	misc QH426-470 misc V2F misc immunogenetics misc TCR misc eQTL misc sQTL misc Genetics
topic_unstemmed	misc QH426-470 misc V2F misc immunogenetics misc TCR misc eQTL misc sQTL misc Genetics
topic_browse	misc QH426-470 misc V2F misc immunogenetics misc TCR misc eQTL misc sQTL misc Genetics
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	Genes
hierarchy_parent_id	614096537
hierarchy_top_title	Genes
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)614096537 (DE-600)2527218-4
title	Functional Genetics to Understand the Etiology of Autoimmunity
ctrlnum	(DE-627)DOAJ087359197 (DE-599)DOAJ6844f53851054c6b8cdc54785aac56d1
title_full	Functional Genetics to Understand the Etiology of Autoimmunity
author_sort	Hiroaki Hatano
journal	Genes
journalStr	Genes
callnumber-first-code	Q
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2023
contenttype_str_mv	txt
author_browse	Hiroaki Hatano Kazuyoshi Ishigaki
container_volume	14
class	QH426-470
format_se	Elektronische Aufsätze
author-letter	Hiroaki Hatano
doi_str_mv	10.3390/genes14030572
author2-role	verfasserin
title_sort	functional genetics to understand the etiology of autoimmunity
callnumber	QH426-470
title_auth	Functional Genetics to Understand the Etiology of Autoimmunity
abstract	Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review.
abstractGer	Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review.
abstract_unstemmed	Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review.
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700
container_issue	3, p 572
title_short	Functional Genetics to Understand the Etiology of Autoimmunity
url	https://doi.org/10.3390/genes14030572 https://doaj.org/article/6844f53851054c6b8cdc54785aac56d1 https://www.mdpi.com/2073-4425/14/3/572 https://doaj.org/toc/2073-4425
remote_bool	true
author2	Kazuyoshi Ishigaki
author2Str	Kazuyoshi Ishigaki
ppnlink	614096537
callnumber-subject	QH - Natural History and Biology
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.3390/genes14030572
callnumber-a	QH426-470
up_date	2024-07-04T01:21:42.303Z
_version_	1803609547533713408
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ087359197</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240413051450.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230331s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/genes14030572</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ087359197</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ6844f53851054c6b8cdc54785aac56d1</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QH426-470</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Hiroaki Hatano</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Functional Genetics to Understand the Etiology of Autoimmunity</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of <i<HLA</i< genes and (ii) non-coding variants at the non-<i<HLA</i< loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how <i<HLA</i< coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">V2F</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">immunogenetics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">TCR</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">eQTL</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">sQTL</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Genetics</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Kazuyoshi Ishigaki</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Genes</subfield><subfield code="d">MDPI AG, 2010</subfield><subfield code="g">14(2023), 3, p 572</subfield><subfield code="w">(DE-627)614096537</subfield><subfield code="w">(DE-600)2527218-4</subfield><subfield code="x">20734425</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:14</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:3, p 572</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/genes14030572</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/6844f53851054c6b8cdc54785aac56d1</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/2073-4425/14/3/572</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2073-4425</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">14</subfield><subfield code="j">2023</subfield><subfield code="e">3, p 572</subfield></datafield></record></collection>
score	7.401388

Nicht das Richtige dabei?

Schreiben Sie uns!

Functional Genetics to Understand the Etiology of Autoimmunity

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?