Advanced genetics (Hoboken, N.J.)最新文献

The co-occurrence of sensorineural hearing loss and male infertility has been reported in several instances, suggesting potential shared genetic underpinnings. One such example is the contiguous gene deletion of CATSPER2 and STRC genes, previously associated with deafness-infertility syndrome (DIS) in males. Fifteen males with both hearing loss and infertility from southern India after exclusion for the DIS contiguous gene deletion and the FOXI1 gene mutations are subjected to exome sequencing. This resolves the genetic etiology in four probands for both the phenotypes; In the remaining 11 probands, two each conclusively accounted for deafness and male infertility etiologies. Genetic heterogeneity is well reflected in both phenotypes. Four recessive (TRIOBP, SLC26A4, GJB2, COL4A3) and one dominant (SOX10) for the deafness; six recessive genes (LRGUK, DNAH9, ARMC4, DNAH2, RSPH6A, and ACE) for male infertility can be conclusively ascribed. LRGUK and RSPH6A genes are implicated earlier only in mice models, while the ARMC4 gene is implicated in chronic destructive airway diseases due to primary ciliary dyskinesia. This study would be the first to document the role of these genes in the male infertility phenotype in humans. The result suggests that deafness and infertility are independent events and do not segregate together among the probands.

The social movement to reduce reliance on pesticides and synthesized fertilizers and the growing global demand for sustainable food supplies require the development of eco-friendly and sustainable agricultural practices. In line, plant growth-promoting bacteria (PGPB) can participate in creating innovative agroecological systems. While the effectiveness of PGPB is highly influenced by abiotic conditions and microbe–microbe interactions, beneficial plant–PGPB interactions can also highly depend on both host and PGPB genotype. Here, the state of the art on the extent of natural genetic variation of plant–PGPB interactions and the underlying genetic architecture, in particular in Arabidopsis thaliana is reviewed. Extensive natural plant genetic variation in response to PGPB is associated with a polygenic architecture and genetic pathways rarely mentioned as being involved in the response to PGPB. To date, natural genetic variation within PGPB is little explored, which may in turn allow the identification of new genetic pathways underlying benefits to plants. Accordingly, several avenues to better understand the genomic and molecular landscape of plant–PGPB interactions are introduced. Finally, the need for establishing thorough functional studies of candidate genes underlying Quantitative Trait Loci and estimating the extent of genotype-by-genotype-by-environment interactions within the context of realistic (agro-)ecological conditions is advocated.

Ultraviolet (UV) light is the most pervasive environmental mutagen and the primary cause of skin cancer. Genome sequencing of melanomas and other skin cancers has revealed that the vast majority of somatic mutations in these tumors are cytosine-to-thymine (C>T) substitutions in dipyrimidine sequences, which, together with tandem CC>TT substitutions, comprise the canonical UV mutation “signature”. These mutation classes are caused by DNA damage directly induced by UV absorption, namely cyclobutane pyrimidine dimers (CPDs) or 6-4 pyrimidine-pyrimidone photoproducts (6-4PP), which form between neighboring pyrimidine bases. However, many of the key driver mutations in melanoma do not fit this mutation signature, but instead are caused by T>A, T>C, C>A, or AC>TT substitutions, frequently occurring in non-dipyrimidine sequence contexts. This article describes recent studies indicating that UV light causes a more diverse spectrum of mutations than previously appreciated, including many of the mutation classes observed in melanoma driver mutations. Potential mechanisms for these diverse mutation signatures are discussed, including UV-induced pyrimidine-purine photoproducts and indirect DNA damage induced by UVA light. Finally, the article reviews recent findings indicating that human DNA polymerase eta normally suppresses these non-canonical UV mutation classes, which can potentially explain why canonical C>T substitutions predominate in human skin cancers.

Cancer is one of the foremost causes of mortality. The human genome remains stable over time. However, human activities and environmental factors have the power to influence the prevalence of certain types of mutations. This goes to the excessive progress of xenobiotics and industrial development that is expanding the territory for cancers to develop. The mechanisms involved in immune responses against cancer are widely studied. Genome editing has changed the genome-based immunotherapy process in the human body and has opened a new era for cancer treatment. In this review, recent cancer immunotherapies and the use of genome engineering technology are largely focused on.

Plant biology studies in the post-genome era have been focused on annotating genome sequences’ functions. The established plant mutant collections have greatly accelerated functional genomics research in the past few decades. However, most plant genome sequences' roles and the underlying regulatory networks remain substantially unknown. Clustered, regularly interspaced short palindromic repeat (CRISPR)-associated systems are robust, versatile tools for manipulating plant genomes with various targeted DNA perturbations, providing an excellent opportunity for high-throughput interrogation of DNA elements’ roles. This study compares methods frequently used for plant functional genomics and then discusses different DNA multi-targeted strategies to overcome gene redundancy using the CRISPR-Cas9 system. Next, this work summarizes recent reports using CRISPR libraries for high-throughput gene knockout and function discoveries in plants. Finally, this work envisions the future perspective of optimizing and leveraging CRISPR library screening in plant genomes' other uncharacterized DNA sequences.

Deep learning (DL) approaches have the ability to accurately recognize promoter regions and predict their strength. Here, the potential for controllably designing active Escherichia coli promoter is explored by combining multiple deep learning models. First, “DRSAdesign,” which relies on a diffusion model to generate different types of novel promoters is created, followed by predicting whether they are real or fake and strength. Experimental validation showed that 45 out of 50 generated promoters are active with high diversity, but most promoters have relatively low activity. Next, “Ndesign,” which relies on generating random sequences carrying functional −35 and −10 motifs of the sigma70 promoter is introduced, and their strength is predicted using the designed DL model. The DL model is trained and validated using 200 and 50 generated promoters, and displays Pearson correlation coefficients of 0.49 and 0.43, respectively. Taking advantage of the DL models developed in this work, possible 6-mers are predicted as key functional motifs of the sigma70 promoter, suggesting that promoter recognition and strength prediction mainly rely on the accommodation of functional motifs. This work provides DL tools to design promoters and assess their functions, paving the way for DL-assisted metabolic engineering.