Microbiome markers in HPV-positive and HPV-negative women of reproductive age with ASCUS and SIL determined by V4 region of 16S rRNA gene sequencing.

Introduction: Human papilloma virus (HPV) is the most common sexually transmitted infection worldwide. Cervicovaginal microbiota plays an important role in HPV infection and is associated with the development of squamous intraepithelial lesions (SIL). The natural history of cervical cancer involves reversible changes in the cervical tissue from a normal state, in which no neoplastic changes are detected in the squamous epithelium, to varying states of cellular abnormalities that ultimately lead to cervical cancer. Low-grade SIL (LSIL), like another cytological category - atypical squamous cells of undetermined significance (ASCUS), may progress to high-grade SIL (HSIL) and invasive cervical cancer or may regress to a normal state. Methods: In this work, we studied cervical canal microbiome in 165 HPV-positive and HPV-negative women of a reproductive age with ASCUS [HPV(+) n = 29; HPV(-) n = 11], LSIL [HPV(+) n = 32; HPV(-) n = 25], HSIL [HPV(+) n = 46], and the control group with negative for intraepithelial lesion malignancy (NILM) [HPV(-) n = 22]. Results and Discussion: HPV16 is the most prevalent HPV type. We have not found any differences between diversity in studied groups, but several genus [like Prevotella (p-value = 0.026), Gardnerella (p-value = 0.003), Fannyhessea (p-value = 0.024)] more often occurred in HSIL group compared by NILM or LSIL regardless of HPV. We have found statistically significant difference in occurrence or proportion of bacterial genus in studied groups. We also identified that increasing of the ratio of Lactobacillus iners or age of patient lead to higher chance to HSIL, while increasing of the ratio of Lactobacillus crispatus lead to higher chance to LSIL. Patients with a moderate dysbiosis equally often had either of three types of vaginal microbial communities (CST, Community State Type) with the prevalence of Lactobacillus crispatus (CST I), Lactobacillus gasseri (CST II), and Lactobacillus iners (CST III); whereas severe dysbiosis is linked with CST IV involving the microorganisms genera associated with bacterial vaginosis and aerobic vaginitis: Gardnerella, Fannyhessea, Dialister, Sneathia, Anaerococcus, Megasphaera, Prevotella, Finegoldia, Peptoniphilus, Porphyromonas, Parvimonas, and Streptococcus.

Candidate Genes for IgA Nephropathy in Pediatric Patients: Exome-Wide Association Study.

IgA nephropathy (IgAN) is an autoimmune disorder which is believed to be non-monogenic. We performed an exome-wide association study of 70 children with IgAN and 637 healthy donors. The HLA allele frequencies were compared between the patients and healthy donors from the bone marrow registry of the Pirogov University. We tested 78,020 gene markers for association and performed functional enrichment analysis and transcription factor binding preference detection. We identified 333 genetic variants, employing three inheritance models. The most significant association with the disorder was observed for rs143409664 (PRAG1) in the case of the additive and dominant models (PBONF = 1.808 × 10-15 and PBONF = 1.654 × 10-15, respectively), and for rs13028230 (UBR3) in the case of the recessive model (PBONF = 1.545 × 10-9). Enrichment analysis indicated the strongly overrepresented "immune system" and "kidney development" terms. The HLA-DQA1*01:01:01G allele (p = 0.0076; OR, 2.021 [95% CI, 1.322-3.048]) was significantly the most frequent among IgAN patients. Here, we characterized, for the first time, the genetic background of Russian IgAN patients, identifying the risk alleles typical of the population. The most important signals were detected in previously undescribed loci.

The Search of Association of HLA Class I and Class II Alleles with COVID-19 Mortality in the Russian Cohort.

HLA genes play a pivotal role in the immune response via presenting the pathogen peptides on the cell surface in a host organism. Here, we studied the association of HLA allele variants of class I (loci A, B, C) and class II (loci DRB1, DQB1, DPB1) genes with the outcome of COVID-19 infection. We performed high-resolution sequencing of class HLA I and class II genes based on the sample population of 157 patients who died from COVID-19 and 76 patients who survived despite severe symptoms. The results were further compared with HLA genotype frequencies in the control population represented by 475 people from the Russian population. Although the obtained data revealed no significant differences between the samples at a locus level, they allowed one to uncover a set of notable alleles potentially contributing to the COVID-19 outcome. Our results did not only confirm the previously discovered fatal role of age or association of DRB1*01:01:01G and DRB1*01:02:01G alleles with severe symptoms and survival, but also allowed us to single out the DQB1*05:03:01G allele and B*14:02:01G~C*08:02:01G haplotype, which were associated with survival. Our findings showed that not only separate allele, but also their haplotype, could serve as potential markers of COVID-19 outcome and be used during triage for hospital admission.

Description of the novel HLA-C allele, HLA-C*12:376, identified in a deceased COVID-19 patient.

The new allele HLA-C*12:376 showed one nonsynonymous nucleotide difference compared with the C*12:03:01:01 allele in codon 30.

Description of the novel allele HLA-B*07:473, identified in a bone marrow donor.

The new HLA-B*07:473 allele showed two nonsynonymous nucleotide differences compared with the HLA-B*07:02:01:01 allele in codon 116.

Performance comparison of Agilent new SureSelect All Exon v8 probes with v7 probes for exome sequencing.

Exome sequencing is becoming a routine in health care, because it increases the chance of pinpointing the genetic cause of an individual patient's condition and thus making an accurate diagnosis. It is important for facilities providing genetic services to keep track of changes in the technology of exome capture in order to maximize throughput while reducing cost per sample. In this study, we focused on comparing the newly released exome probe set Agilent SureSelect Human All Exon v8 and the previous probe set v7. In preparation for higher throughput of exome sequencing using the DNBSEQ-G400, we evaluated target design, coverage statistics, and variants across these two different exome capture products. Although the target size of the v8 design has not changed much compared to the v7 design (35.24 Mb vs 35.8 Mb), the v8 probe design allows you to call more of SNVs (+ 3.06%) and indels (+ 8.49%) with the same number of raw reads per sample on the common target regions (34.84 Mb). Our results suggest that the new Agilent v8 probe set for exome sequencing yields better data quality than the current Agilent v7 set.

System analysis of the sequencing quality of human whole exome samples on BGI NGS platform.

Human exome sequencing is a classical method used in most medical genetic applications. The leaders in the field are the manufacturers of enrichment kits based on hybridization of cRNA or cDNA biotinylated probes specific for a genomic region of interest. Recently, the platforms manufactured by the Chinese company MGI Tech have become widespread in Europe and Asia. The reliability and quality of the obtained data are already beyond any doubt. However, only a few kits compatible with these sequencers can be used for such specific tasks as exome sequencing. We developed our own solution for library pre-capture pooling and exome enrichment with Agilent probes. In this work, using a set of the standard benchmark samples from the Platinum Genome collection, we demonstrate that the qualitative and quantitative parameters of our protocol which we called "RSMU_exome" exceed those of the MGI Tech kit. Our protocol allows for identifying more SNV and indels, generates fewer PCR duplicates, enables pooling of more samples in a single enrichment procedure, and requires less raw data to obtain results comparable with the MGI Tech's protocol. The cost of our protocol is also lower than that of MGI Tech's solution.

Description of a novel allele HLA-DRB1*16:02:10, identified in a bone marrow donor.

The new allele HLA-DRB1*16:02:10 showed one synonymous nucleotide difference with HLA-DRB1*16:02:01:01 in codon 58.

A novel allele, HLA-C*15:227, identified when typing COVID-19 patients.

HLA-C*15:227 differs from HLA-C*15:02:01:01 by a single nonsynonymous change (368A → G Tyrosine 99 to Cysteine).

The novel HLA-DQB1*05:02:24 allele, identified in a Russian bone marrow donor.

The new allele HLA-DQB1*05:02:24 showed one synonymous nucleotide difference with HLA-DQB1*05:02:01:01 in codon 140.

HLA-A*11:382N, a novel HLA-A null allele identified by next-generation sequencing.

The new allele HLA-A*11:382N showed one nucleotide difference with HLA-A*11:01:01:01 at codon 254 (nonsense mutation).

HLA-C*06:287, a novel HLA-C*06 allele identified by sequence-based typing.

The new allele HLA-C*06:287 showed one nucleotide difference with HLA-C*06:02:01:01 at codon 219 (CGG/CAG).

Description of a novel HLA-A allele, HLA-A*03:365, identified in a bone marrow donor from Russia.

The novel allele HLA-A*03:365 showed a single nucleotide difference from A*03:01:01:01 where 135 Alanine is changed to Proline.