scholarly journals Genome-wide Single-Cell Analysis of Recombination Activity and De Novo Mutation Rates in Human Sperm

Cell ◽  
2012 ◽  
Vol 150 (2) ◽  
pp. 402-412 ◽  
Author(s):  
Jianbin Wang ◽  
H. Christina Fan ◽  
Barry Behr ◽  
Stephen R. Quake
BMC Cancer ◽  
2011 ◽  
Vol 11 (1) ◽  
Author(s):  
Geir Olav Hjortland ◽  
Leonardo A Meza-Zepeda ◽  
Klaus Beiske ◽  
Anne H Ree ◽  
Siri Tveito ◽  
...  

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Nobuo Yoshimoto ◽  
Kenji Tatematsu ◽  
Masumi Iijima ◽  
Tomoaki Niimi ◽  
Andrés D. Maturana ◽  
...  

2019 ◽  
Author(s):  
Alice Accorsi ◽  
Andrew C. Box ◽  
Robert Peuß ◽  
Christopher Wood ◽  
Alejandro Sánchez Alvarado ◽  
...  

AbstractImage-based cell classification has become a common tool to identify phenotypic changes in cell populations. However, this methodology is limited to organisms possessing well characterized species-specific reagents (e.g., antibodies) that allow cell identification, clustering and convolutional neural network (CNN) training. In the absence of such reagents, the power of image-based classification has remained mostly off-limits to many research organisms. We have developed an image-based classification methodology we named Image3C (Image-Cytometry Cell Classification) that does not require species-specific reagents nor pre-existing knowledge about the sample. Image3C combines image-based flow cytometry with an unbiased, high-throughput cell cluster pipeline and CNN integration. Image3C exploits intrinsic cellular features and non-species-specific dyes to perform de novo cell composition analysis and to detect changes in cellular composition between different conditions. Therefore, Image3C expands the use of imaged-based analyses of cell population composition to research organisms in which detailed cellular phenotypes are unknown or for which species-specific reagents are not available.Impact statementImage3C analyzes cell populations through image-based clustering and neural network training, which allows single-cell analysis in research organisms devoid of species-specific reagents or pre-existing knowledge on cell phenotypes.


2022 ◽  
pp. gr.276103.121
Author(s):  
Daniel Melamed ◽  
Yuval Nov ◽  
Assaf Malik ◽  
Michael B Yakass ◽  
Evgeni Bolotin ◽  
...  

While it is known that the mutation rate varies across the genome, previous estimates were based on averaging across various numbers of positions. Here we describe a method to measure the origination rates of target mutations at target base positions and apply it to a 6-bp region in the human hemoglobin subunit beta (HBB) gene and to the identical, paralogous hemoglobin subunit delta (HBD) region in sperm cells from both African and European donors. The HBB region of interest (ROI) includes the site of the hemoglobin S (HbS) mutation, which protects against malaria, is common in Africa and has served as a classic example of adaptation by random mutation and natural selection. We found a significant correspondence between de novo mutation rates and past observations of alleles in carriers, showing that mutation rates vary substantially in a mutation-specific manner that contributes to the site frequency spectrum. We also found that the overall point mutation rate is significantly higher in Africans than in Europeans in the HBB region studied. Finally, the rate of the 20A→T mutation, called the 'HbS mutation' when it appears in HBB, is significantly higher than expected from the genome-wide average for this mutation type. Nine instances were observed in the African HBB ROI, where it is of adaptive significance, representing at least three independent originations; no instances were observed elsewhere. Further studies will be needed to examine mutation rates at the single-mutation resolution across these and other loci and organisms and to uncover the molecular mechanisms responsible.


2020 ◽  
Author(s):  
Jennifer N. Berger ◽  
Bridget Sanford ◽  
Abigail K. Kimball ◽  
Lauren M. Oko ◽  
Rachael E. Kaspar ◽  
...  

SUMMARYVirus infection is frequently characterized using bulk cell populations. How these findings correspond to infection in individual cells remains unclear. Here, we integrate high-dimensional single-cell approaches to quantify viral and host RNA and protein expression signatures using de novo infection with a well-characterized model gammaherpesvirus. While infected cells demonstrated genome-wide transcription, individual cells revealed pronounced variation in gene expression, with only 9 of 80 annotated viral open reading frames uniformly expressed in all cells, and a 1000-fold variation in viral RNA expression between cells. Single-cell analysis further revealed positive and negative gene correlations, many uniquely present in a subset of cells. Beyond variation in viral gene expression, individual cells demonstrated a pronounced, dichotomous signature in host gene expression, revealed by measuring host RNA abundance and post-translational protein modifications. These studies provide a resource for the high-dimensional analysis of virus infection, and a conceptual framework to define virus infection as the sum of virus and host responses at the single-cell level.HIGHLIGHTSCyTOF and scRNA-seq identify wide variation in gene expression between infected cells.Host RNA expression and post-translational modifications stratify virus infection.Single cell RNA analysis reveals new relationships in viral gene expression.Simultaneous measurement of virus and host defines distinct infection states.


2021 ◽  
Author(s):  
Daniel Melamed ◽  
Yuval Nov ◽  
Assaf Malik ◽  
Michael B. Yakass ◽  
Evgeni Bolotin ◽  
...  

While it is known that the mutation rate varies across the genome, previous estimates of it were based on averaging across various numbers of positions. Here we describe a method to measure the origination rates of target mutations at target base positions and apply it to a 6-bp region in the human β–globin (HBB) gene and to the identical, homologous δ–globin (HBD) region in sperm cells from both African and European donors. The HBB region of interest (ROI) includes the site of the hemoglobin S (HbS) mutation, which protects against malaria, is common in Africa and has served as a classic example of adaptation by random mutation and natural selection. We found a significant correspondence between de novo mutation rates and past observations of alleles in carriers, showing that mutation rates vary substantially in a mutation-specific manner that contributes to the site frequency spectrum. We also found that the overall point mutation rate is significantly higher in Africans than Europeans in the HBB region studied. Finally, the rate of the 20A→T mutation, called the ″HbS mutation″ when it appears in HBB, is significantly higher than expected from the genome-wide average for this mutation type. Nine instances of it were observed in the African HBB ROI, where it is of adaptive significance, representing at least three independent originations, and no instances of it were observed in the European HBB ROI or in the European or African HBD ROI. Further studies will be needed to examine mutation rates at the single-mutation resolution across these and other loci and organisms and to uncover the molecular mechanisms responsible.


Author(s):  
Alexander Lind ◽  
Falastin Salami ◽  
Anne‐Marie Landtblom ◽  
Lars Palm ◽  
Åke Lernmark ◽  
...  

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