Synthetic Standards Combined With Error and Bias Correction Improve the Accuracy and Quantitative Resolution of Antibody Repertoire Sequencing in Human Naïve and Memory B Cells

High-throughput sequencing of immunoglobulin (Ig) repertoires (Ig-seq) is a powerful method for quantitatively interrogating B cell receptor sequence diversity. When applied to human repertoires, Ig-seq provides insight into fundamental immunological questions, and can be implemented in diagnostic and drug discovery projects. However, a major challenge in Ig-seq is ensuring accuracy, as library preparation protocols and sequencing platforms can introduce substantial errors and bias that compromise immunological interpretation. Here, we have established an approach for performing highly accurate human Ig-seq by combining synthetic standards with a comprehensive error and bias correction pipeline. First, we designed a set of 85 synthetic antibody heavy-chain standards (in vitro transcribed RNA) to assess correction workflow fidelity. Next, we adapted a library preparation protocol that incorporates unique molecular identifiers (UIDs) for error and bias correction which, when applied to the synthetic standards, resulted in highly accurate data. Finally, we performed Ig-seq on purified human circulating B cell subsets (naïve and memory), combined with a cellular replicate sampling strategy. This strategy enabled robust and reliable estimation of key repertoire features such as clonotype diversity, germline segment, and isotype subclass usage, and somatic hypermutation. We anticipate that our standards and error and bias correction pipeline will become a valuable tool for researchers to validate and improve accuracy in human Ig-seq studies, thus leading to potentially new insights and applications in human antibody repertoire profiling

CGG Repeat-Induced FMR1 Silencing Depends on the Expansion Size in Human iPSCs and Neurons Carrying Unmethylated Full Mutations

In fragile X syndrome (FXS), CGG repeat expansion greater than 200 triplets is believed to trigger FMR1 gene silencing and disease etiology. However, FXS siblings have been identified with more than 200 CGGs, termed unmethylated full mutation (UFM) carriers, without gene silencing and disease symptoms. Here, we show that hypomethylation of the FMR1 promoter is maintained in induced pluripotent stem cells (iPSCs) derived from two UFM individuals. However, a subset of iPSC clones with large CGG expansions carries silenced FMR1. Furthermore, we demonstrate de novo silencing upon expansion of the CGG repeat size. FMR1 does not undergo silencing during neuronal differentiation of UFM iPSCs, and expression of large unmethylated CGG repeats has phenotypic consequences resulting in neurodegenerative features. Our data suggest that UFM individuals do not lack the cell-intrinsic ability to silence FMR1 and that inter-individual variability in the CGG repeat size required for silencing exists in the FXS population

High-throughput sequencing error and bias correction increases the quantitative resolution of human naïve and memory B-cell receptor repertoires

Accurate high-throughput sequencing of immunoglobulin (Ig) chains (Ig-Seq) is often problematic due to primer bias and sequencing errors. Human Ig sequencing is further complicated by factors such as greater population-level germline allelic diversity, longer CDR3 regions relative to murine sequences, and a more complex antigenic history combined with higher frequency of somatic hypermutation (SHM), particularly in affinity-matured memory B-cell subsets. As a result, Ig heavy chain repertoire analysis tends to underestimate combinatorial diversity while simultaneously overestimating SHM. To overcome these issues, we developed a workflow for highly accurate human antibody heavy chain sequencing. First, we designed a set of 85 synthetic (in vitro transcribed RNA) Ig heavy chain standards representing all known IGHV and IGHJ alleles, unique CDR3s, and incorporating point mutations to mimic SHM. These standards are used in both isotype-dependent and -independent manners at predetermined ratios as spike-ins with biological samples to control for sequencing accuracy. Next, we prepared antibody libraries from purified circulating human B cells and spike-in RNA using a protocol known as molecular amplification fingerprinting (MAF), which incorporates unique molecular identifiers before and during multiplexed PCR amplification. We then performed MAF-based error and bias correction, and cellular replicate sampling to generate a robust, reliable, and highly accurate analysis of human antibody repertoires. We applied the workflow to estimate clonal diversity, gene segment usage, and SHM in naïve (IgM+ CD27-) and memory (IgG+ CD27+) B-cell subsets isolated from three different donors. Based on the sampling size, we are able to estimate the clonal diversity of the human naïve B-cell repertoire and that of the IgG memory B-cell repertoire combined with the level of SHM

Presentation_1_Synthetic Standards Combined With Error and Bias Correction Improve the Accuracy and Quantitative Resolution of Antibody Repertoire Sequencing in Human Naïve and Memory B Cells.PDF

<p>High-throughput sequencing of immunoglobulin (Ig) repertoires (Ig-seq) is a powerful method for quantitatively interrogating B cell receptor sequence diversity. When applied to human repertoires, Ig-seq provides insight into fundamental immunological questions, and can be implemented in diagnostic and drug discovery projects. However, a major challenge in Ig-seq is ensuring accuracy, as library preparation protocols and sequencing platforms can introduce substantial errors and bias that compromise immunological interpretation. Here, we have established an approach for performing highly accurate human Ig-seq by combining synthetic standards with a comprehensive error and bias correction pipeline. First, we designed a set of 85 synthetic antibody heavy-chain standards (in vitro transcribed RNA) to assess correction workflow fidelity. Next, we adapted a library preparation protocol that incorporates unique molecular identifiers (UIDs) for error and bias correction which, when applied to the synthetic standards, resulted in highly accurate data. Finally, we performed Ig-seq on purified human circulating B cell subsets (naïve and memory), combined with a cellular replicate sampling strategy. This strategy enabled robust and reliable estimation of key repertoire features such as clonotype diversity, germline segment, and isotype subclass usage, and somatic hypermutation. We anticipate that our standards and error and bias correction pipeline will become a valuable tool for researchers to validate and improve accuracy in human Ig-seq studies, thus leading to potentially new insights and applications in human antibody repertoire profiling.</p

Human neurons carrying FMR1 unmethylated full mutations require large CGG repeat expansions for silencing and display neurodegenerative features

In Fragile X Syndrome (FXS), unmethylated full mutation (UFM) individuals carry a CGG expansion greater than 200 repeats in the FMR1 gene but lack the disease causing DNA methylation mediated silencing. Here, we show that hypomethylation of the FMR1 promoter is maintained in induced pluripotent stem cells (iPSCs) derived from two UFM individuals. However, we identify a subset of iPSC clones with large CGG expansions that silence FMR1. Furthermore, we demonstrate that de-novo silencing occurs upon expansion of CGG repeats. The silencing status of FMR1 is stable during neuronal differentiation. This indicates that UFM stem cells do not undergo developmental silencing as described for FXS. We also show that the expression of large unmethylated CGG repeats has direct phenotypic consequences resulting in neurodegenerative features. Our data suggest that UFM individuals do not lack the ability to silence FMR1 but require a higher CGG repeat size than the one described for FXS patients