The killer-cell immunoglobulin-like receptor (KIR) gene complex, located in human chromosomal region 19q13.42, and the complement component 4 (C4) gene complex, located in human chromosomal region 6p21.33, encode for proteins that have vital roles in immune system function. Component genes of these complexes exhibit copy number variation (CNV), extensive nucleotide polymorphisms, and high sequence similarity with other genes of their complex. Next generation sequencing (NGS) has transformed the world of genomics, offering a high-throughput, high-fidelity and cost-effective sequencing method, however, NGS analysis of the KIR and C4 regions has been thwarted due to the bioinformatics challenges imposed by their complex variation. In this work, the researcher presents the bioinformatics pipelines, PING, developed for KIR sequence analysis, and C4Investigator, developed for C4 sequence analysis. These bioinformatics pipelines provide comprehensive, high-throughput characterization of human KIR and C4 sequence variation from NGS data. These pipelines take in paired-end short-read sequencing data and output gene copy number for both genomic regions, high-resolution genotypes for the KIR complex, and high-resolution mapping of single nucleotide variants (SNVs) for the C4 region. The performance of PING was evaluated by real-world and synthetic datasets, while the performance of C4Investigator was evaluated by real-world datasets and comparison to existing methods. Both PING and C4Investigator showed high performance for copy number determination and SNV characterization. To demonstrate the utility of the C4Investigator pipeline, the researcher applied C4Investigator to whole genome sequencing (WGS) data from the 1000 Genomes Project (1KGP) cohort (N=3199), characterizing C4 copy number and sequence variation for the first time in this dataset. To demonstrate the utility of the PING pipeline, the researched applied PING to targeted sequencing datasets from divergent populations (European N=363, Khoesan N=104), in addition to WGS data from the 1KGP cohort (N=215). To the best of our knowledge, PING and C4Investigator are the only bioinformatics workflows currently available for assessment of KIR and C4 full genomic sequence variation from NGS data.

Although the primary protein sequence of ubiquitin (Ub) is extremely stable over evolutionary time, it is highly tolerant to mutation during selection experiments performed in the laboratory. We have proposed that this discrepancy results from the difference between fitness under laboratory culture conditions and the selective pressures in changing environments over evolutionary timescales. Building on our previous work (Mavor et al., 2016), we used deep mutational scanning to determine how twelve new chemicals (3-Amino-1,2,4-triazole, 5-fluorocytosine, Amphotericin B, CaCl₂, Cerulenin, Cobalt Acetate, Menadione, Nickel Chloride, p-Fluorophenylalanine, Rapamycin, Tamoxifen, and Tunicamycin) reveal novel mutational sensitivities of ubiquitin residues. Collectively, our experiments have identified eight new sensitizing conditions for Lys63 and uncovered a sensitizing condition for every position in Ub except Ser57 and Gln62. By determining the ubiquitin fitness landscape under different chemical constraints, our work helps to resolve the inconsistencies between deep mutational scanning experiments and sequence conservation over evolutionary timescales.