A deep learning framework for predicting human essential genes from population and functional genomic data

Being able to predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve our ability to identify genes associated with genetic disorders. Numerous computational methods have recently been developed to predict human essential genes from population genomic data; however, the existing methods have limited power in pinpointing short essential genes due to the sparsity of polymorphisms in the human genome. Here we present an evolution-based deep learning model, DeepLOF, which integrates population and functional genomic data to improve gene essentiality prediction. Compared to previous methods, DeepLOF shows unmatched performance in predicting ClinGen haploinsufficient genes, mouse essential genes, and essential genes in human cell lines. Furthermore, DeepLOF discovers 109 potentially essential genes that are too short to be identified by previous methods. Altogether, DeepLOF is a powerful computational method to aid in the discovery of essential genes.

Genome-wide analysis of fitness-factors in uropathogenic Escherichia coli during growth in laboratory media and during urinary tract infections

Uropathogenic Escherichia coli (UPEC) UTI89 is a well-characterized strain, which has mainly been used to study UPEC virulence during urinary tract infection (UTI). However, little is known on UTI89 key fitness-factors during growth in lab media and during UTI. Here, we used a transposon-insertion-sequencing approach (TraDIS) to reveal the UTI89 essential-genes for in vitro growth and fitness-gene-sets for growth in Luria broth (LB) and EZ-MOPS medium without glucose, as well as for human bacteriuria and mouse cystitis. A total of 293 essential genes for growth were identified and the set of fitness-genes was shown to differ depending on the growth media. A modified, previously validated UTI murine model, with administration of glucose prior to infection was applied. Selected fitness-genes for growth in urine and mouse-bladder colonization were validated using deletion-mutants. Novel fitness-genes, such as tusA, corA and rfaG; involved in sulphur-acquisition, magnesium-uptake, and LPS-biosynthesis, were proved to be important during UTI. Moreover, rfaG was confirmed as relevant in both niches, and therefore it may represent a target for novel UTI-treatment/prevention strategies.

A novel CRISPRi platform to study the role of essential genes in antifungal drug-resistant Candida albicans isolates

With the emergence of antifungal resistant Candida albicans strains, the need for new antifungal drugs is critical in combating this fungal pathogen. Investigating essential genes in C. albicans is a vital step in characterizing putative antifungal drug targets. As some of these essential genes are conserved between fungal organisms, developed therapies targeting these genes have the potential to be broad range antifungals. In order to study these essential genes, classical genetic knockout or CRISPR-based approaches cannot be used as disrupting essential genes leads to lethality in the organism. Fortunately, a variation of the CRISPR system (CRISPR interference or CRISPRi) exists that enables precise transcriptional repression of the gene of interest without introducing genetic mutations. CRISPRi utilizes an endonuclease dead Cas9 protein that can be targeted to a precise location but lacks the ability to create a double-stranded break. The binding of the dCas9 protein to DNA prevents the binding of RNA polymerase to the promoter through steric hindrance thereby reducing expression. We recently published the novel use of this technology in C. albicans and are currently working on expanding this technology to large scale repression of essential genes. Through the construction of an essential gene CRISPRi-sgRNA library, we can begin to study the function of essential genes under different conditions and identify genes that are involved in critical processes such as drug tolerance in antifungal resistant background strains. These genes can ultimately be characterized as putative targets for novel antifungal drug development, or targeted as a means to sensitize drug-resistant strains to antifungal treatment.

Hierarchical length and sequence preferences establish a single major piRNA 3'-end

PIWI-interacting RNAs (piRNAs) guard germline genomes against the deleterious action of retroviruses and other mobile genetic elements. How piRNAs faithfully discriminate between self and non-self to restrict all mobile elements while sparing essential genes remains a key outstanding question in genome biology. PiRNAs use extensive base-pairing to recognize their targets and variable 3'ends could change the specificity and efficacy of piRNA silencing. Here, we identify conserved rules that ensure the generation of a single major piRNA 3'end in flies and mice. Our data suggest that the PIWI proteins initially define a short interval on pre-piRNAs that grants access to the ZUC-processor complex. Within this Goldilocks zone, the preference of the ZUC-processor to cut in front of a Uridine determines the ultimate processing site. We observe a mouse-specific roadblock that relocates the Goldilocks zone and generates an opportunity for consecutive trimming by PNLDC1. Our data reveal a conserved hierarchy between length and sequence preferences that controls the piRNA sequence space. The unanticipated precision of 3'end formation bolsters the emerging understanding that the functional piRNA sequence space is tightly controlled to ensure effective defense.

Research on the Computational Prediction of Essential Genes

Genes, the nucleotide sequences that encode a polypeptide chain or functional RNA, are the basic genetic unit controlling biological traits. They are the guarantee of the basic structures and functions in organisms, and they store information related to biological factors and processes such as blood type, gestation, growth, and apoptosis. The environment and genetics jointly affect important physiological processes such as reproduction, cell division, and protein synthesis. Genes are related to a wide range of phenomena including growth, decline, illness, aging, and death. During the evolution of organisms, there is a class of genes that exist in a conserved form in multiple species. These genes are often located on the dominant strand of DNA and tend to have higher expression levels. The protein encoded by it usually either performs very important functions or is responsible for maintaining and repairing these essential functions. Such genes are called persistent genes. Among them, the irreplaceable part of the body’s life activities is the essential gene. For example, when starch is the only source of energy, the genes related to starch digestion are essential genes. Without them, the organism will die because it cannot obtain enough energy to maintain basic functions. The function of the proteins encoded by these genes is thought to be fundamental to life. Nowadays, DNA can be extracted from blood, saliva, or tissue cells for genetic testing, and detailed genetic information can be obtained using the most advanced scientific instruments and technologies. The information gained from genetic testing is useful to assess the potential risks of disease, and to help determine the prognosis and development of diseases. Such information is also useful for developing personalized medication and providing targeted health guidance to improve the quality of life. Therefore, it is of great theoretical and practical significance to identify important and essential genes. In this paper, the research status of essential genes and the essential genome database of bacteria are reviewed, the computational prediction method of essential genes based on communication coding theory is expounded, and the significance and practical application value of essential genes are discussed.