The Y-chromosome is a widely studied and useful small part of the genome providing different applications for interdisciplinary research. In many (Western) societies, the Y-chromosome and surnames are paternally coinherited, suggesting a corresponding Y-haplotype for every namesake. While it has already been observed that this correlation may be disrupted by a false-paternity event, adoption, anonymous sperm donor or the cofounding of surnames, extensive information on the strength of the surname match frequency (SMF) with the Ychromosome remains rather unknown. For the first time in Belgium and the Netherlands, we were able to study this correlation using 2,401 males genotyped for 46 Y-STRs and 183 Y-SNPs. The SMF was observed to be dependent on the number of Y-STRs analyzed, their mutation rates and the number of Y-STR differences allowed for a kinship. For a perfect match, the Yfiler® Plus and our in-house YForGen kit gave a similar high SMF of 98%, but for non-perfect matches, the latter could overall be identified as the best kit. The SMF generally increased due to less mismatches when encountering [1] deep Y-subhaplogroups, [2] less frequently occurring surnames, and [3] small geographical distances between relatives. This novel information enabled the design of a surname prediction model based on genetic and geographical distances of a kinship. The prediction model has an area under the curve (AUC) of 0.9 and is therefore useable for DNA kinship priority listing in estimation applications like forensic familial searching.
Short tandem repeats on the Y-chromosome (Y-STRs) are common DNA polymorphisms useful for genetic genealogy, population and evolutionary genetics, human genetics, pathology and forensic sciences. It is important to identify all Y-STR variants and to have knowledge of Y-STR mutation rates in order to correctly estimate the time to the most recent common ancestor (tMRCA) between paternally related individuals. When capillary electrophoresis (CE) is performed to analyze genealogical pairs, Y-STR sequence variations remain hidden when the number of repeats is identical. These hidden variations could be due to parallel Y-STR changes or modifications (PM) that occur independently in different lineages leading to alleles with identical number of repeats. In this study, we detect for the first time twelve PM by analyzing 133 males (960 meiosis) in extended deep-rooting family pedigrees on 42 Y-STRs. These PM were observed in nine Y-STR loci with mutation rates of at least 5.94 × 10 −3 per generation. Sequencing analysis made it possible to distinguish insertions/ deletions in different repeat regions revealing the presence of two unique changes in three PM on rapidly mutating and complex Y-STRs DYS724-ab and DYS518. Sequencing unraveled more information concerning the identity of alleles, and increased allelic discrimination possibilities which is of great importance in population genetics and forensic analysis. Limiting the analysis to CE could lead to wrong ancestral allele assumptions, to false negative interpretations and to tMRCA underestimations. These observations highlight the importance and added value of sequencing analysis and suggest a shift in genotyping methods from CE to next generation sequencing.
The frequent acquisition of genomic abnormalities in human preimplantation embryos is a leading cause of pregnancy loss, but does not necessarily prohibit healthy offspring. However, the impact of genomic abnormalities on cellular states and development of the early human embryo remains largely unclear. Here, we characterise aneuploidy and reconstruct gene regulatory networks in human preimplantation embryos, and investigate gene expression and developmental perturbations instigated by aneuploidy using single-cell genome-and-transcriptome sequencing (G&T-seq). At the genomic level, we show that acquired numerical and structural chromosomal aberrations are frequent across all stages of early embryogenesis and in all cell lineages. At the transcriptome level, we identify regulators of cell identity and uncover a network of 248 transcription factors from 10 major gene regulatory modules that characterise the distinct lineages of human preimplantation embryos. By integrating single-cell DNA- with RNA-information, we unveil how expression levels are affected by losses or gains of the corresponding genes in embryonic cells across human preimplantation development, as well as how copy-number aberrant transcription factor genes perturb the expression of their cognate target genes in euploid regions. Furthermore, we reveal a majority of aneuploid cells show a developmental delay and reduced fitness, indicating cell competition within the mosaic diploid-aneuploid embryo, which may contribute to selection against aneuploid cells and the birth of healthy offspring from mosaic diploid-aneuploid embryos. In summary, our multi-modal analyses provide unprecedented insights into early human embryo development.
Single-cell multi-omics methods are enabling the study of cell state diversity, which is largely determined by the interplay of the genome, epigenome, and transcriptome. Here, we describe Gtag&T-seq, a genome-and-transcriptome sequencing (G&T-seq) protocol of the same single cells that omits whole-genome amplification (WGA) by using direct genomic tagmentation (Gtag). Gtag drastically decreases the cost and improves coverage uniformity at both the single-cell and pseudo-bulk level when compared to WGA-based G&T-seq. We also show that transcriptome-based DNA copy number inference has limited resolution and accuracy, underlining the importance of affordable multi-omic approaches. Moreover, applying Gtag&T-seq to a melanoma xenograft model before treatment and at minimal residual disease revealed differential cell state plasticity and treatment response between cancer subclones. In summary, Gtag&T-seq is a low-cost and accurate single-cell multi-omics method enabling the exploration of genetic alterations and their functional consequences in single cells at scale.
Study question Which are the transcriptional signatures of chromosome instability (CIN) on the human pre-implantation embryo biology at single-cell level? Summary answer CIN-perturbed cells show gene expression dosage effects as well as signatures of developmental delay and cell competition within the developing human embryo. What is known already According to studies analysing whole human embryos at single-cell resolution, as much as 90% of the Day3-4 and up to 100% of the Day6-12 carry one or more cells with mitotic abnormalities. Intriguingly, embryonic CIN does not necessarily preclude normal offspring, since ∼30% of mosaic blastocysts detected by preimplantation genetic testing for aneuploidy (PGT-A) can result in healthy live births. A model of post-implantation human development revealed cell selection mechanisms that deplete aneuploid cells from the germ layers. However, single-cell multi-omics approaches have not yet been applied to resolve the transcriptional signatures of CIN in human embryos. Study design, size, duration Cryopreserved human embryos donated for research were dissociated into single cells between Day1-7 post-fertilization. Cells were processed by scG&T-seq generating 295 genomes and 576 transcriptomes. This data was integrated with published single-cell RNA-seq data, totalling 2105 single-cell transcriptomes from 172 embryos. Inference of cells' DNA copy number (CN) from gene expression was benchmarked using G&T-seq data and used for cells lacking DNA-seq data. Participants/materials, setting, methods Effects of aneuploidies on gene expression, regulatory programs, lineage specification and developmental progression rates were studied by integrative analysis on single-cell whole genome copy number and whole transcriptome data. Main results and the role of chance On the genomic level, we observed frequent acquired numerical and structural chromosomal aberrations. Deletions were more frequent than duplications and were equally spread across pre-implantation stages and cell lineages. Although 88% of the embryos contained aneuploid cells, 63% still contained euploid cells. On the transcriptome level, we disclosed 248 active transcription factors (TFs), including key regulators of cell identity, that constitute 10 major gene regulatory modules driving pre-implantation development. By integrating single-cell DNA-plus-RNA information, we unveil that changes in genes’ CN directly result in transcriptional changes in the same direction, and we disclose aberrant gene regulation. Moreover, we observed cell competition instigating well before ICM/TE cell lineages specification. Common transcriptomic signatures within CIN-perturbed cells were identified. Interestingly, in TE, cell competition signatures co-existed with up-regulation of pro-proliferative and implantation-related genes. Limitations, reasons for caution Our study is based on single-cell whole genome expression data from disaggregated IVF pre-implantation embryos. Wider implications of the findings Our analyses suggest that while unfit CIN-perturbed cells might be eliminated by cell competition mechanisms, these might be tolerated and potentially beneficial in TE. Thus, encouraging the transfer of mosaic embryos after PGT-A. Besides, we provide a unique comprehensive data resource for future work. Trial registration number not applicable
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