Genetic alterations that affect the function of p53 tumor suppressor have been extensively investigated in myeloid neoplasms, revealing their significant impact on disease progression, treatment response, and patient outcomes. The identification and characterization of TP53 mutations play pivotal roles in subclassifying myeloid neoplasms and guiding treatment decisions. Starting with the presentation of a typical case, this review highlights the complicated nature of genetic alterations involving TP53 and provides a comprehensive analysis of TP53 mutations and other alterations in myeloid neoplasms. Currently available methods used in clinical laboratories to identify TP53 mutations are discussed, focusing on the importance of establishing a robust testing protocol within clinical laboratories to ensure the delivery of accurate and reliable results. The treatment implications of TP53 mutations in myeloid neoplasms and clinical trial options are reviewed. Ultimately, we hope that this review provides valuable insights into the patterns of TP53 alterations in myeloid neoplasms and offers guidance to establish practical laboratory testing protocols to support the best practices of precision oncology.

Aureobasidium pullulans is a ubiquitous polymorphic black yeast with industrial and agricultural applications. It has recently gained attention amongst cell biologists for its unconventional mode of proliferation in which multinucleate yeast cells make multiple buds within a single cell cycle. Here, we combine a chemical transformation method with genome-targeted homologous recombination to yield ∼60 transformants/μg of DNA in just 3 days. This protocol is simple, inexpensive, and requires no specialized equipment. We also describe vectors with codon-optimized green and red fluorescent proteins for A. pullulans and use these tools to explore novel cell biology. Quantitative imaging of a strain expressing cytosolic and nuclear markers showed that although the nuclear number varies considerably among cells of similar volume, total nuclear volume scales with cell volume over an impressive 70-fold size range. The protocols and tools described here expand the toolkit for A. pullulans biologists and will help researchers address the many other puzzles posed by this polyextremotolerant and morphologically plastic organism.

This chapter overviews genetic techniques\' fundamentals and methodological features, including different approaches, analyses, and applications that have contributed to advancing health and disease. The aim is to describe laboratory methodologies and analyses employed to understand the genetic landscape of different biological contexts, from conventional techniques to cutting-edge technologies. Besides describing detailed aspects of the polymerase chain reaction (PCR) and derived types as one of the principles for many novel techniques, we also discuss microarray analysis, next-generation sequencing, and genome editing technologies such as transcription activator-like effector nucleases (TALENs) and the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) systems. These techniques study several phenotypes, ranging from autoimmune disorders to viral diseases. The significance of integrating diverse genetic methodologies and tools to understand host genetics comprehensively and addressing the ethical, legal, and social implications (ELSI) associated with using genetic information is highlighted. Overall, the methods, procedures, and applications in host genetic analysis provided in this chapter furnish researchers and practitioners with a roadmap for navigating the dynamic landscape of host-genome interactions.

Telomeres are located at the ends of chromosomes and have specific sequences with a distinctive structure that safeguards genes. They possess capping structures that protect chromosome ends from fusion events and ensure chromosome stability. Telomeres shorten in length during each cycle of cell division. When this length reaches a certain threshold, it can lead to genomic instability, thus being implicated in various diseases, including cancer and neurodegenerative disorders. The possibility of telomeres serving as a biomarker for aging and age-related disease is being explored, and their significance is still under study. This is because post-mitotic cells, which are mature cells that do not undergo mitosis, do not experience telomere shortening due to age. Instead, other causes, for example, exposure to oxidative stress, can directly damage the telomeres, causing genomic instability. Nonetheless, a general agreement has been established that measuring telomere length offers valuable insights and forms a crucial foundation for analyzing gene expression and epigenetic data. Numerous approaches have been developed to accurately measure telomere lengths. In this review, we summarize various methods and their advantages and limitations for assessing telomere length.

Modern medicine has produced large genetic datasets of high dimensions through advanced gene sequencing technology, and processing these data is of great significance for clinical decision-making. Gene selection (GS) is an important data preprocessing technique that aims to select a subset of feature information to improve performance and reduce data dimensionality. This study proposes an improved wrapper GS method based on forensic-based investigation (FBI). The method introduces the search mechanism of the slime mould algorithm in the FBI to improve the original FBI; the newly proposed algorithm is named SMA_FBI; then GS is performed by converting the continuous optimizer to a binary version of the optimizer through a transfer function. In order to verify the superiority of SMA_FBI, experiments are first executed on the 30-function test set of CEC2017 and compared with 10 original algorithms and 10 state-of-the-art algorithms. The experimental results show that SMA_FBI is better than other algorithms in terms of finding the optimal solution, convergence speed, and robustness. In addition, BSMA_FBI (binary version of SMA_FBI) is compared with 8 binary algorithms on 18 high-dimensional genetic data from the UCI repository. The results indicate that BSMA_FBI is able to obtain high classification accuracy with fewer features selected in GS applications. Therefore, SMA_FBI is considered an optimization tool with great potential for dealing with global optimization problems, and its binary version, BSMA_FBI, can be used for GS tasks.

Brainbow is a genetic cell-labeling technique that allows random colorization of multiple cells and real-time visualization of cell fate within a tissue, providing valuable insights into understanding complex biological processes. However, fluorescent proteins (FPs) in Brainbow have distinct excitation spectra with peak difference greater than 35 nm, which requires sequential imaging under multiple excitations and thus leads to long acquisition times. In addition, they are not easily used together with other fluorophores due to severe spectral bleed-through. Here, we report the development of a single-wavelength excitable Brainbow, UFObow, incorporating three newly developed blue-excitable FPs. We have demonstrated that UFObow enables not only tracking the growth dynamics of tumor cells in vivo but also mapping spatial distribution of immune cells within a sub-cubic centimeter tissue, revealing cell heterogeneity. This provides a powerful means to explore complex biology in a simultaneous imaging manner at a single-cell resolution in organs or in vivo.

Microbial products are essential for developing various therapeutic agents, including antibiotics, anticancer drugs, vaccines, and therapeutic enzymes. Genetic engineering techniques, functional genomics, and synthetic biology unlock previously uncharacterized natural products. This review highlights major advances in microbial biotechnology, focusing on gene-based technologies for medical applications.

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Although fungi have been important model organisms for solving genetic, molecular, and ecological problems, recently, they are also becoming an important source of infectious disease. Despite their high medical burden, fungal pathogens are understudied, and relative to other pathogenic microbes, less is known about how their gene functions contribute to disease. This is due, in part, to a lack of powerful genetic tools to study these organisms. In turn, this has resulted in inappropriate treatments and diagnostics and poor disease management. There are a variety of reasons genetic studies were challenging in pathogenic fungi, but in recent years, most of them have been overcome or advances have been made to circumvent these barriers. In this minireview, we highlight how recent advances in genetic studies in fungal pathogens have resulted in the discovery of important biology and potential new antifungals and have created the tools to comprehensively study these important pathogens.

The microtubule motor dynein plays a key role in cellular organization. However, little is known about how dynein\'s biosynthesis, assembly, and functional diversity are orchestrated. To address this issue, we have conducted an arrayed CRISPR loss-of-function screen in human cells using the distribution of dynein-tethered peroxisomes and early endosomes as readouts. From a genome-wide gRNA library, 195 validated hits were recovered and parsed into those impacting multiple dynein cargoes and those whose effects are restricted to a subset of cargoes. Clustering of high-dimensional phenotypic fingerprints revealed co-functional proteins involved in many cellular processes, including several candidate novel regulators of core dynein functions. Further analysis of one of these factors, the RNA-binding protein SUGP1, indicates that it promotes cargo trafficking by sustaining functional expression of the dynein activator LIS1. Our data represent a rich source of new hypotheses for investigating microtubule-based transport, as well as several other aspects of cellular organization captured by our high-content imaging.