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Krjutshkov, K.

Publications and source records attributed to Krjutshkov, K..

2 recordsLinked to original sources

Creating basis for introducing NIPT in the Estonian public health setting

ObjectiveThe study aimed to validate a whole-genome sequencing-based NIPT method and our newly developed NIPTmer analysis software with the potential to integrate the pipeline into prenatal clinical care in Estonia.\n\nMethodIn total, 447 maternal blood samples were included to the study. Analysis pipeline involved whole-genome library preparation and massively parallel sequencing on Illumina NextSeq 500. Aneuploidy status was determined with NIPTmer software, which is based on counting pre-defined per-chromosome sets of unique k-mers from raw sequencing data. To estimate fetal fraction (FF) from total cell-free DNA SeqFF was implemented.\n\nResultsNIPTmer software allowed to identify correctly all samples of non-mosaic T21 (15/15), T18 (9/9) and T13 (4/4) cases. However, one mosaic T18 remained undetected. Six false positive results were observed, including three for T18 (specificity 99.3%) and three for T13 (specificity 99.3%). FF < 4% (2.8-3.99%) was estimated in eight samples, including two samples with T13 and T18. Despite low FF, these two samples were determined as aneuploid with NIPTmer software.\n\nConclusionOur NIPT analysis pipeline proved to perform efficiently in detecting common fetal aneuploidies T21, T18 and T13 and is feasible for implementation into clinical service in Estonia.

genetics

Endometrial receptivity revisited: endometrial transcriptome adjusted for tissue cellular heterogeneity

STUDY QUESTIONDoes cellular composition of the endometrial biopsy affect the gene expression profile of endometrial whole-tissue samples?\n\nSUMMARY ANSWERThe differences in epithelial and stromal cell proportions in endome-trial biopsies modify whole-tissue gene expression profiles, and also affect the results of differential expression analysis.\n\nWHAT IS ALREADY KNOWNEach cell type has its unique gene expression profile. The proportions of epithelial and stromal cells vary in endometrial tissue during the menstrual cycle, along with individual and technical variation due to the way and tools used to obtain the tissue biopsy.\n\nSTUDY DESIGN, SIZE, DURATIONUsing cell-population specific transcriptome data and computational deconvolution approach, we estimated the epithelial and stromal cell proportions in whole-tissue biopsies taken during early secretory and mid-secretory phases. The estimated cellular proportions were used as covariates in whole-tissue differential gene expression analysis. Endometrial transcriptomes before and after deconvolution were compared and analysed in biological context.\n\nPARTICIPANTS/MATERIAL, SETTING, METHODSPaired early- and mid-secretory endometrial biopsies were obtained from thirty-five healthy, regularly cycling, fertile volunteers, aged 23 to 36 years, and analysed by RNA sequencing. Differential gene expression analysis was performed using two approaches. In one of them, computational deconvolution was applied as an intermediate step to adjust for epithelial and stromal cells proportions in endometrial biopsy. The results were then compared to conventional differential expression analysis.\n\nMAIN RESULTS AND THE ROLE OF CHANCEThe estimated average proportions of stromal and epithelial cells in early secretory phase were 65% and 35%, and during mid-secre-tory phase 46% and 54%, respectively, that correlated well with the results of histological evaluation (r=0.88, p=1.1x10-6). Endometrial tissue transcriptomic analysis showed that approximately 26% of transcripts (n=946) differentially expressed in receptive endometrium in cell-type unadjusted analysis also remain differentially expressed after adjustment for biopsy cellular composition. However, the other 74% (n=2,645) become statistically non-significant after adjustment for biopsy cellular composition, underlining the impact of tissue heterogeneity on differential expression analysis. The results suggest new mechanisms involved in endometrial maturation involving genes like LINC01320, SLC8A1 and GGTA1P, described for the first time in context of endometrial receptivity.\n\nLIMITATIONS, REASONS FOR CAUTIONOnly dominant endometrial cell types were considered in gene expression profile deconvolution; however, other less frequent endometrial cell types also contribute to the whole-tissue gene expression profile.\n\nWIDER IMPLICATIONS OF THE FINDINGSThe better understanding of molecular processes during transition from pre-receptive to receptive endometrium serves to improve the effectiveness and personalization of assisted reproduction protocols. Biopsy cellular composition should be taken into account in future endometrial omics studies, where tissue heterogeneity could potentially influence the results.\n\nTRIAL REGISTRATION NON/A

genomics