Transgenerational gene expression depends on both underlying DNA sequences and epigenetic modifications. The latter, which can result in transmission of variegated gene expression patterns across multiple generations without DNA alterations, has been termed epigenetic inheritance and has been documented in plants, worms, flies and mammals. Whereas transcription factors binding to cognate DNA sequence elements regulate gene expression, the molecular basis for epigenetic inheritance has been linked to histone and DNA modifications and non-coding RNA. Here we report that mutation of the CCAAT box promoter element abrogates NF-Y binding and disrupts the stable transgenerational expression of an MHC class I transgene. Transgenic mice with a mutated CCAAT box in the MHC class I transgene display variegated expression of the transgene among littermates and progeny in multiple independently derived transgenic lines. After 4 generations, CCAAT mutant transgenic lines derived from a single founder stably displayed distinct patterns of expression. Histone modifications and RNA polymerase II binding correlate with expression of CCAAT mutant transgenic lines, whereas DNA methylation and nucleosome occupancy do not. Mutation of the CCAAT box also results in changes to CTCF binding and DNA looping patterns across the transgene that correlate with expression status. These studies identify the CCAAT promoter element as a regulator of stable transgenerational gene expression such that mutation of the CCAAT box results in variegated transgenerational inheritance. Considering that the CCAAT box is present in 30% of eukaryotic promoters, this study provides insights into how fidelity of gene expression patterns is maintained through multiple generations.

Dog leukocyte antigen (DLA) polymorphisms have been found to be associated with inter-individual variations in the risk, susceptibility, and severity of immune-related phenomena. While DLA class II genes have been extensively studied, less research has been performed on the polymorphisms of DLA class I genes, especially in beagle dogs commonly used as laboratory animals for safety evaluations in drug development. We genotyped four DLA class I genes and four DLA class II genes by locus-specific Sanger sequencing using 93 laboratory beagle dogs derived from two different strains: TOYO and Marshall. The results showed that, for DLA class I genes, 11, 4, 1, and 2 alleles, including a novel allele, were detected in DLA-88, DLA-12/88L, DLA-64, and DLA-79, while, for DLA class II genes, 1, 10, 6, and 7 alleles were detected in DLA-DRA, DLA-DRB1, DLA-DQA1, and DLA-DQB1, respectively. It was estimated that there were 14 DLA haplotypes, six of which had a frequency of ≥ 5%. Furthermore, when comparing the DLA diversity between TOYO and Marshall strains, the most common alleles and haplotypes differed between them. This is the first study to genotype all DLA loci and determine DLA haplotypes including all DLA class I and class II genes in dogs. Integrating information on the DLA diversity of laboratory beagle dogs should reinforce their benefit as an animal model for understanding various diseases associated with a specific DLA type.

Human leukocyte antigen (HLA) typing is of great importance in clinical applications such as organ transplantation, blood transfusion, disease diagnosis and treatment, and forensic analysis. In recent years, nanopore sequencing technology has emerged as a rapid and cost-effective option for HLA typing. However, due to the principles and data characteristics of nanopore sequencing, there was a scarcity of robust and generalizable bioinformatics tools for its downstream analysis, posing a significant challenge in deciphering the thousands of HLA alleles present in the human population. To address this challenge, we developed NanoHLA as a tool for high-resolution typing of HLA class I genes without error correction based on nanopore sequencing. The method integrated the concepts of HLA type coverage analysis and the data conversion techniques employed in Nano2NGS, which was characterized by applying nanopore sequencing data to NGS-liked data analysis pipelines. In validation with public nanopore sequencing datasets, NanoHLA showed an overall concordance rate of 84.34% for HLA-A, HLA-B, and HLA-C, and demonstrated superior performance in comparison to existing tools such as HLA-LA. NanoHLA provides tools and solutions for use in HLA typing related fields, and look forward to further expanding the application of nanopore sequencing technology in both research and clinical settings. The code is available at https://github.com/langjidong/NanoHLA .

HLA-B*58:02:04 differs from HLA-B*58:02:01 by one synonymous nucleotide in codon 215 in exon 4.

The HLA-B*40:538 allele differs from HLA-B*40:01:02:01 at position 905 C→T in exon 5.

The novel HLA-B*13:191 allele was detected during the HLA typing for kidney transplantation.

HLA-C*06:376N differs from HLA-C*06:02:01:01 by seven nucleotide changes in exon 2, intron 2, and exon 3.

HLA-C*03:94:02 differs from HLA-C*03:94:01 by a single nucleotide substitution in exon 2 (codon 17 GGA->GGG).

Novel HLA-B*55:01:31, HLA-C*07:1113 alleles and confirmatory HLA-C*12:392 allele were detected during the HLA typing process.

The novel allele HLA-C*07:02:147 differs from HLA-C*07:02:01:01 by one synonymous nucleotide substitution in exon 2.