Househam J, Heide T, Cresswell GD, Spiteri I, Kimberley C, Zapata L, Lynn C, James C, Mossner M, Fernandez-Mateos J, Vinceti A, Baker AM, Gabbutt C, Berner A, Schmidt M, Chen B, Lakatos E, Gunasri V, Nichol D, Costa H, Mitchinson M, Ramazzotti D, Werner B, Iorio F, Jansen M, Caravagna G, Barnes CP, Shibata D, Bridgewater J, Rodriguez-Justo M, Magnani L, Sottoriva A, Graham TA. (2022) Phenotypic plasticity and genetic control in colorectal cancer evolution. Nature [Epub ahead of print]. [article]
From The Scientist by Jef Akst
Most models of how tumors evolve have assumed that the process is based predominately on cancer cells’ genetics, and many cancer treatments are specifically targeted to mutations associated with disease. But comparing whole genome sequence data with RNA-seq data from samples of colorectal tumors revealed that the vast majority of gene expression differences among cancer cells cannot be explained by genetics, researchers report in Nature today (October 26).
To gain a better understanding of how cancer cells vary at the gene expression level, the team carried out whole-transcript RNA-seq as well as whole genome sequencing on samples from 27 surgically removed human colorectal tumors, eight of which yielded sufficient data for comparisons between the two types of sequencing. In those eight tumors, out of 8,368 differentially expressed genes included in the analysis, the differences in transcript levels could be traced to underlying genetics in only a median of 166.
(read more…)
Househam J, Heide T, Cresswell GD, Spiteri I, Kimberley C, Zapata L, Lynn C, James C, Mossner M, Fernandez-Mateos J, Vinceti A, Baker AM, Gabbutt C, Berner A, Schmidt M, Chen B, Lakatos E, Gunasri V, Nichol D, Costa H, Mitchinson M, Ramazzotti D, Werner B, Iorio F, Jansen M, Caravagna G, Barnes CP, Shibata D, Bridgewater J, Rodriguez-Justo M, Magnani L, Sottoriva A, Graham TA. (2022) Phenotypic plasticity and genetic control in colorectal cancer evolution. Nature [Epub ahead of print]. [article]
Heide T, Househam J, Cresswell GD, Spiteri I, Lynn C, Mossner M, Kimberley C, Fernandez-Mateos J, Chen B, Zapata L, James C, Barozzi I, Chkhaidze K, Nichol D, Gunasri V, Berner A, Schmidt M, Lakatos E, Baker AM, Costa H, Mitchinson M, Piazza R, Jansen M, Caravagna G, Ramazzotti D, Shibata D, Bridgewater J, Rodriguez-Justo M, Magnani L, Graham TA, Sottoriva A. (2022) The co-evolution of the genome and epigenome in colorectal cancer. Nature [Epub ahead of print]. [article]
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From The Scientist by Jef Akst
Most models of how tumors evolve have assumed that the process is based predominately on cancer cells’ genetics, and many cancer treatments are specifically targeted to mutations associated with disease. But comparing whole genome sequence data with RNA-seq data from samples of colorectal tumors revealed that the vast majority of gene expression differences among cancer cells cannot be explained by genetics, researchers report in Nature today (October 26).
To gain a better understanding of how cancer cells vary at the gene expression level, the team carried out whole-transcript RNA-seq as well as whole genome sequencing on samples from 27 surgically removed human colorectal tumors, eight of which yielded sufficient data for comparisons between the two types of sequencing. In those eight tumors, out of 8,368 differentially expressed genes included in the analysis, the differences in transcript levels could be traced to underlying genetics in only a median of 166.
(read more…)
Househam J, Heide T, Cresswell GD, Spiteri I, Kimberley C, Zapata L, Lynn C, James C, Mossner M, Fernandez-Mateos J, Vinceti A, Baker AM, Gabbutt C, Berner A, Schmidt M, Chen B, Lakatos E, Gunasri V, Nichol D, Costa H, Mitchinson M, Ramazzotti D, Werner B, Iorio F, Jansen M, Caravagna G, Barnes CP, Shibata D, Bridgewater J, Rodriguez-Justo M, Magnani L, Sottoriva A, Graham TA. (2022) Phenotypic plasticity and genetic control in colorectal cancer evolution. Nature [Epub ahead of print]. [article]
Heide T, Househam J, Cresswell GD, Spiteri I, Lynn C, Mossner M, Kimberley C, Fernandez-Mateos J, Chen B, Zapata L, James C, Barozzi I, Chkhaidze K, Nichol D, Gunasri V, Berner A, Schmidt M, Lakatos E, Baker AM, Costa H, Mitchinson M, Piazza R, Jansen M, Caravagna G, Ramazzotti D, Shibata D, Bridgewater J, Rodriguez-Justo M, Magnani L, Graham TA, Sottoriva A. (2022) The co-evolution of the genome and epigenome in colorectal cancer. Nature [Epub ahead of print]. [article]
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Small RNA sequencing reveals regulatory roles for sdRNAs in acute myeloid leukemia
POND-seq enables non-destructive RNA sequencing in living cells
Worm’s radical transformation shows metamorphosis can change the functions of cells
New method allows scientists to follow gene activity over time in the same cells
Single-cell and single-embryo RNA sequencing
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Deep learning improves microRNA target prediction from sequence
Atlas of the brain’s striatum could guide researchers to new drug treatments
scLS – a computationally efficient differentially expressed gene detection algorithm
Spatial mapping of RNA turnover kinetics in the mouse brain
Immune cells offer insights on billion-dollar virus
SPIDER improves spatial transcriptomics data using single-cell RNA sequencing
Ultrafast and reference-free sequence discovery in single-cell data
ARCADIA combines RNA sequencing and spatial proteomics to reveal how tissue location shapes cell behavior
An end-to-end computational framework for “Record-seq” transcriptional recording data
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
ExoShorkie – predicting RNA-seq coverage of exogenous genomes in yeast by transfer learning
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Bonsai reconstructs tree representations for distortion-free visualization and exploration of high-dimensional data
MiRQuery – a user-friendly web app for the interactive analysis and visualization of microRNA sequencing data
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