An intron is any nucleotide sequence within a gene that is not expressed or operative in the final RNA product. The word intron is derived from the term intragenic region, i.e., a region inside a gene. The term intron refers to both the DNA sequence within a gene and the corresponding RNA sequence in RNA transcripts. The non-intron sequences that become joined by this RNA processing to form the mature RNA are called exons.
MicroRNA (miRNA) are small, single-stranded, non-coding RNA molecules containing 21 to 23 nucleotides. Found in plants, animals and some viruses, miRNAs are involved in RNA silencing and post-transcriptional regulation of gene expression. miRNAs base-pair to complementary sequences in mRNA molecules, then gene silence said mRNA molecules by one or more of the following processes:
- Cleavage of mRNA strand into two pieces,
- Destabilization of mRNA by shortening its poly(A) tail, or
- Translation of mRNA into proteins.
A generegulatory network (GRN) is a collection of molecular regulators that interact with each other and with other substances in the cell to govern the gene expression levels of mRNA and proteins which, in turn, determine the function of the cell. GRN also play a central role in morphogenesis, the creation of body structures, which in turn is central to evolutionary developmental biology (evo-devo).
James Joseph Collins is an American bioengineer who serves as the Termeer Professor of Medical Engineering & Science at the Massachusetts Institute of Technology (MIT). Collins conducted research showing that artificial intelligence (AI) approaches can be used to discover novel antibiotics, such as halicin and abaucin. He serves as the Director of the Antibiotics-AI Project at MIT, which is supported by The Audacious Project, and is the faculty lead for life sciences at the MIT Jameel Clinic.
Tropomyosin alpha-3 chain is a protein that in humans is encoded by the TPM3 gene.
Myosin-Ic is a protein that in humans is encoded by the MYO1C gene.
Developmental noise or stochastic noise is a concept within developmental biology in which the observable characteristics or traits (phenotype) varies between individuals even though both individuals share the same genetic code (genotypes) and the other environmental factors are completely the same. Factors that influence the effect include stochastic, or randomized, gene expression and other cellular noise.
Transcriptional bursting, also known as transcriptional pulsing, is a fundamental property of genes in which transcription from DNA to RNA can occur in "bursts" or "pulses", which has been observed in diverse organisms, from bacteria to mammals.
Transcriptional noise is a primary cause of the variability (noise) in gene expression occurring between cells in isogenic populations. A proposed source of transcriptional noise is transcriptional bursting although other sources of heterogeneity, such as unequal separation of cell contents at mitosis are also likely to contribute considerably. Bursting transcription, as opposed to simple probabilistic models of transcription, reflects multiple states of gene activity, with fluctuations between states separated by irregular intervals, generating uneven protein expression between cells. Noise in gene expression can have tremendous consequences on cell behaviour, and must be mitigated or integrated. In certain contexts, such as establishment of viral latency, the survival of microbes in rapidly changing stressful environments, or several types of scattered differentiation, the variability may be essential. Variability also impacts upon the effectiveness of clinical treatment, with resistance of bacteria and yeast to antibiotics demonstrably caused by non-genetic differences. Variability in gene expression may also contribute to resistance of sub-populations of cancer cells to chemotherapy and appears to be a barrier to curing HIV.
Michael B. Elowitz is a biologist and professor of Biology, Bioengineering, and Applied Physics at the California Institute of Technology, and investigator at the Howard Hughes Medical Institute. In 2007 he was the recipient of the Genius grant, better known as the MacArthur Fellows Program for the design of a synthetic gene regulatory network, the Repressilator, which helped initiate the field of synthetic biology. In addition, he showed, for the first time, how inherently random effects, or 'noise', in gene expression could be detected and quantified in living cells, leading to a growing recognition of the many roles that noise plays in living cells. His work in Synthetic Biology and Noise represent two foundations of the field of Systems Biology. Since then, his laboratory has contributed to the development of synthetic biological circuits that perform a range of functions inside cells, and revealed biological circuit design principles underlying epigenetic memory, cell fate control, cell-cell communication, and multicellular behaviors.
In evolutionary biology, robustness of a biological system is the persistence of a certain characteristic or trait in a system under perturbations or conditions of uncertainty. Robustness in development is known as canalization. According to the kind of perturbation involved, robustness can be classified as mutational, environmental, recombinational, or behavioral robustness etc. Robustness is achieved through the combination of many genetic and molecular mechanisms and can evolve by either direct or indirect selection. Several model systems have been developed to experimentally study robustness and its evolutionary consequences.
Cellular noise is random variability in quantities arising in cellular biology. For example, cells which are genetically identical, even within the same tissue, are often observed to have different expression levels of proteins, different sizes and structures. These apparently random differences can have important biological and medical consequences.
Johan Paulsson is a Swedish mathematician and systems biologist at Harvard Medical School. He is a leading researcher in systems biology and stochastic processes, specializing in stochasticity in gene networks and plasmid reproduction.
Single-cell sequencing examines the nucleic acid sequence information from individual cells with optimized next-generation sequencing technologies, providing a higher resolution of cellular differences and a better understanding of the function of an individual cell in the context of its microenvironment. For example, in cancer, sequencing the DNA of individual cells can give information about mutations carried by small populations of cells. In development, sequencing the RNAs expressed by individual cells can give insight into the existence and behavior of different cell types. In microbial systems, a population of the same species can appear genetically clonal. Still, single-cell sequencing of RNA or epigenetic modifications can reveal cell-to-cell variability that may help populations rapidly adapt to survive in changing environments.
State switching is a fundamental physiological process in which a cell/organism undergoes spontaneous, and potentially reversible, transitions between different phenotypes. Thus, the ability to switch states/phenotypes is a key feature of development and normal function of cells within most multicellular organisms that enables the cell to respond to various intrinsic and extrinsic cues and stimuli in a concerted fashion enabling them to ‘make’ appropriate cellular decisions. Although state switching is essential for normal functioning, the repertoire of phenotypes in a normal cell is albeit limited.
Debora S. Marks is a researcher in computational biology and a Professor of Systems Biology at Harvard Medical School. Her research uses computational approaches to address a variety of biological problems.
Single-cell transcriptomics examines the gene expression level of individual cells in a given population by simultaneously measuring the RNA concentration of hundreds to thousands of genes. Single-cell transcriptomics makes it possible to unravel heterogeneous cell populations, reconstruct cellular developmental pathways, and model transcriptional dynamics — all previously masked in bulk RNA sequencing.
Spatial transcriptomics is a method for assigning cell types to their locations in the histological sections. This method can also be used to determine subcellular localization of mRNA molecules. The term is a variation of Spatial Genomics, first described by Doyle, et al., in 2000 and then expanded upon by Ståhl et al. in a technique developed in 2016, which has since undergone a variety of improvements and modifications.
Transcriptional memory is a biological phenomenon, initially discovered in yeast, during which cells primed with a particular cue show increased rates of gene expression after re-stimulation at a later time. This event was shown to take place: in yeast during growth in galactose and inositol starvation; plants during environmental stress; in mammalian cells during LPS and interferon induction. Prior work has shown that certain characteristics of chromatin may contribute to the poised transcriptional state allowing faster re-induction. These include: activity of specific transcription factors, retention of RNA polymerase II at the promoters of poised genes, activity of chromatin remodeling complexes, propagation of H3K4me2 and H3K36me3 histone modifications, occupancy of the H3.3 histone variant, as well as binding of nuclear pore components. Moreover, locally bound cohesin was shown to inhibit establishment of transcriptional memory in human cells during interferon gamma stimulation.
