Statistical analysis of repertoire data demonstrates the influence of microhomology in V(D)J recombination

V(D)J recombination generates the diverse B and T cell receptors essential for recognizing a wide array of antigens. This diversity arises from the combinatorial assembly of V(D)J genes and the junctional deletion and insertion of nucleotides. While previous in vitro studies have shown that microhomology---short stretches of sequence homology between gene ends---can bias the recombination process, the extent of microhomologys impact in vivo, particularly in humans, remains unknown. In this paper, we assess how germline-encoded microhomology influences trimming and ligation during V(D)J recombination using statistical inference on previously-published high-throughput TCR repertoire sequencing data. We find that microhomology increases both trimming and ligation probabilities, making it an important predictor of recombination outcomes. These effects are consistent across different receptor loci and sequence types. Further, we demonstrate that accounting for microhomology effects significantly alters sequence annotation probabilities and rankings, highlighting its practical importance for accurately inferring the V(D)J recombination events that generated an observed sequence. Together, these results enhance our understanding of how microhomologous nucleotides shape the human V(D)J recombination process. Significance StatementHumans rely on diverse adaptive immune receptor repertoires to effectively defend against infections. The receptor generation process, known as V(D)J recombination, is designed to create this diversity by stochastically joining V(D)J gene segments and modifying their junctions through nucleotide deletions and insertions. Previous studies, conducted in vitro, have suggested that short stretches of homologous nucleotides between gene segments can bias these recombination steps. In this study, we explore the extent to which these homologous nucleotides influence V(D)J recombination in humans using statistical inference on large-scale receptor repertoire sequencing data. Our findings reveal that microhomology significantly biases several recombination steps, with important practical implications for the analysis, processing, and interpretation of receptor sequences.