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免疫球蛋白基因座中的基因预测。

Gene prediction in the immunoglobulin loci.

机构信息

Computer Science and Engineering Department, University of California San Diego, San Diego, California 92093, USA.

The Department of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA.

出版信息

Genome Res. 2022 Jun;32(6):1152-1169. doi: 10.1101/gr.276676.122. Epub 2022 May 11.

Abstract

The V(D)J recombination process rearranges the variable (V), diversity (D), and joining (J) genes in the immunoglobulin (IG) loci to generate antibody repertoires. Annotation of these loci across various species and predicting the V, D, and J genes (IG genes) are critical for studies of the adaptive immune system. However, because the standard gene finding algorithms are not suitable for predicting IG genes, they have been semimanually annotated in very few species. We developed the IGDetective algorithm for predicting IG genes and applied it to species with the assembled IG loci. IGDetective generated the first large collection of IG genes across many species and enabled their evolutionary analysis, including the analysis of the "bat IG diversity" hypothesis. This analysis revealed extremely conserved V genes in evolutionary distant species, indicating that these genes may be subjected to the same selective pressure, for example, pressure driven by common pathogens. IGDetective also revealed extremely diverged V genes and a new family of evolutionary conserved V genes in bats with unusual noncanonical cysteines. Moreover, unlike all other previously reported antibodies, these cysteines are located within complementarity-determining regions. Because cysteines form disulfide bonds, we hypothesize that these cysteine-rich V genes might generate antibodies with noncanonical conformations and could potentially form a unique part of the immune repertoire in bats. We also analyzed the diversity landscape of the recombination signal sequences and revealed their features that trigger the high/low usage of the IG genes.

摘要

V(D)J 重组过程会对免疫球蛋白 (IG) 基因座中的可变 (V)、多样性 (D) 和连接 (J) 基因进行重排,从而产生抗体库。对不同物种的这些基因座进行注释并预测 V、D 和 J 基因(IG 基因)对于研究适应性免疫系统至关重要。然而,由于标准的基因预测算法并不适用于预测 IG 基因,因此这些基因仅在极少数物种中被进行了半自动注释。我们开发了 IGDetective 算法来预测 IG 基因,并将其应用于具有组装 IG 基因座的物种。IGDetective 生成了跨越许多物种的第一个大型 IG 基因集合,并能够对其进行进化分析,包括对“蝙蝠 IG 多样性”假说的分析。该分析揭示了进化上相距甚远的物种中极其保守的 V 基因,表明这些基因可能受到相同的选择压力,例如由共同病原体驱动的压力。IGDetective 还揭示了在具有异常非典型半胱氨酸的蝙蝠中高度分化的 V 基因和一个新的进化保守 V 基因家族。此外,与所有其他先前报道的抗体不同,这些半胱氨酸位于互补决定区 (CDR) 内。由于半胱氨酸形成二硫键,我们假设这些富含半胱氨酸的 V 基因可能会产生具有非典型构象的抗体,并可能成为蝙蝠免疫系统中独特的一部分。我们还分析了重组信号序列的多样性景观,并揭示了它们触发 IG 基因高/低使用的特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07a5/9248892/48a39745dc46/1152f01.jpg

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