Allelic exclusion of immunoglobulin genes: models and mechanisms

Vettermann, Christian; Schlissel, Mark S.

doi:10.1111/j.1600-065x.2010.00935.x

Cited by 141 publications

(143 citation statements)

References 208 publications

(292 reference statements)

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“…Further mechanisms that contribute to the generation of diversity include alternative IgHD reading frames and IgHD–IgHD fusions 8. These pre‐B‐cells are selected for functional heavy‐chain by IgV‐D‐J expression and IgH assembly by pairing 9, 10…”

Section: Introductionmentioning

confidence: 99%

Antibody repertoire analysis in polygenic autoimmune diseases

2018

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SummaryHigh‐throughput sequencing of the DNA/RNA encoding antibody heavy‐ and light‐chains is rapidly transforming the field of adaptive immunity. It can address key questions, including: (i) how the B‐cell repertoire differs in health and disease; and (ii) if it does differ, the point(s) in B‐cell development at which this occurs. The advent of technologies, such as whole‐genome sequencing, offers the chance to link abnormalities in the B‐cell antibody repertoire to specific genomic variants and polymorphisms. Here, we discuss the current research using B‐cell antibody repertoire sequencing in three polygenic autoimmune diseases where there is good evidence for a pathological role for B‐cells, namely systemic lupus erythematosus, multiple sclerosis and rheumatoid arthritis. These autoimmune diseases exhibit significantly skewed B‐cell receptor repertoires compared with healthy controls. Interestingly, some common repertoire defects are shared between diseases, such as elevated IGHV4‐34 gene usage. B‐cell clones have effectively been characterized and tracked between different tissues and blood in autoimmune disease. It has been hypothesized that these differences may signify differences in B‐cell tolerance; however, the mechanisms and implications of these defects are not clear.

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Section: Introductionmentioning

confidence: 99%

Antibody repertoire analysis in polygenic autoimmune diseases

2018

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“…In cis-eQTL, the allelic expression is regulated in cis (Figure 1b). RMAE (Krueger and Morison, 2008;Chess, 2012) was observed in mouse olfactory receptors (Lomvardas et al, 2006), mammalian X-linked genes that undergo random X chromosome inactivation (Clerc and Avner, 2006), allelic exclusion of immunoglobulin genes (Vettermann and Schlissel, 2010), loss of heterozygosity in cancer (Lasko et al, 1991) and about 8% of the mouse autosomal genes are randomly expressed from one of the parental alleles (Gimelbrant et al, 2007;Zwemer et al, 2012). RMAE generally refers to the situation in which individual cells express one allele or the other, and across a population of cells, both alleles are generally expressed.…”

Section: Quantification Of Dae In Reciprocal Crosses From Inbred or Smentioning

confidence: 99%

“…In some cases, the deviation from 50%:50% is dependent on the parent of origin, such as genomic imprinting (Reik and Walter, 2001;Barlow, 2011;Bartolomei and Ferguson-Smith, 2011) and imprinted X chromosome inactivation (Wake et al, 1976;Huynh and Lee, 2001;Xue et al, 2002;Dindot et al, 2004;Wang et al, 2013a). In other cases, the AI is random or sequence dependent, such as random X chromosome inactivation (Heard et al, 1997), autosomal random monoallelic expression (RMAE; Gimelbrant et al, 2007), allelic exclusion of immunoglobulin genes (Vettermann and Schlissel, 2010), cis-regulating expression quantitative trait loci (cis-eQTL), loss of heterozygosity in cancer (Thiagalingam et al, 2001) and monoallelic expression of olfactory receptors (Chess et al, 1994). Technical details of the methods for quantifying differential allelic expression (DAE) accurately are critical to study AI.…”

Section: Introductionmentioning

confidence: 99%

Using next-generation RNA sequencing to identify imprinted genes

2014

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Genomic imprinting is manifested as differential allelic expression (DAE) depending on the parent-of-origin. The most direct way to identify imprinted genes is to directly score the DAE in a context where one can identify which parent transmitted each allele. Because many genes display DAE, simply scoring DAE in an individual is not sufficient to identify imprinted genes. In this paper, we outline many technical aspects of a scheme for identification of imprinted genes that makes use of RNA sequencing (RNA-seq) from tissues isolated from F1 offspring derived from the pair of reciprocal crosses. Ideally, the parental lines are from two inbred strains that are not closely related to each other. Aspects of tissue purity, RNA extraction, library preparation and bioinformatic inference of imprinting are all covered. These methods have already been applied in a number of organisms, and one of the most striking results is the evolutionary fluidity with which novel imprinted genes are gained and lost within genomes. The general methodology is also applicable to a wide range of other biological problems that require quantification of allele-specific expression using RNA-seq, such as cis-regulation of gene expression, X chromosome inactivation and random monoallelic expression.

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“…Various competing theories on the mechanism of IgH chain allelic exclusion have been proposed, and they are not necessarily mutually exclusive (7). In a stochastic model, allelic exclusion is considered to be a statistical consequence of a low frequency of rearrangements encoding functional H chains (8,9).…”

mentioning

confidence: 99%

Pro-B cells sense productive immunoglobulin heavy chain rearrangement irrespective of polypeptide production

Lutz

Heideman

Roth

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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B-lymphocyte development is dictated by the protein products of functionally rearranged Ig heavy (H) and light (L) chain genes. Ig rearrangement begins in pro-B cells at the IgH locus. If pro-B cells generate a productive allele, they assemble a pre-B cell receptor complex, which signals their differentiation into pre-B cells and their clonal expansion. Pre-B cell receptor signals are also thought to contribute to allelic exclusion by preventing further IgH rearrangements. Here we show in two independent mouse models that the accumulation of a stabilized μH mRNA that does not encode μH chain protein specifically impairs pro-B cell differentiation and reduces the frequency of rearranged IgH genes in a dose-dependent manner. Because noncoding IgH mRNA is usually rapidly degraded by the nonsense-mediated mRNA decay machinery, we propose that the difference in mRNA stability allows pro-B cells to distinguish between productive and nonproductive Ig gene rearrangements and that μH mRNA may thus contribute to efficient H chain allelic exclusion.

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Allelic exclusion of immunoglobulin genes: models and mechanisms

Cited by 141 publications

References 208 publications

Antibody repertoire analysis in polygenic autoimmune diseases

Antibody repertoire analysis in polygenic autoimmune diseases

Using next-generation RNA sequencing to identify imprinted genes

Pro-B cells sense productive immunoglobulin heavy chain rearrangement irrespective of polypeptide production

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