Current Genomics - Volume 24, Issue 4, 2023

Wheat, a crucial crop for the pursuit of food security, is faced with a plateauing yield projected to fall short of meeting the demands of the exponentially increasing human population. To raise global wheat productivity levels, strong efforts must be made to overcome the problems of (1) climate change-induced heat and drought stress and (2) the genotype-dependent amenability of wheat to tissue culture, which limits the success of recovering genetically engineered plants, especially in elite cultivars. Unfortunately, the mainstream approach of genetically engineering plant protein-coding genes may not be effective in solving these problems as it is difficult to map, annotate, functionally verify, and modulate all existing homeologs and paralogs within wheat's large, complex, allohexaploid genome. Additionally, the quantitative, multi-genic nature of most agronomically important traits furthers the complications faced by this approach. miRNAs are small, noncoding RNAs (sncRNAs) that repress gene expression at the post-transcriptional level, regulating various aspects of plant growth and development. They are gaining popularity as alternative targets of genetic engineering efforts for crop improvement due to their (1) highly conserved nature, which facilitates reasonable prediction of their gene targets and phenotypic effects under different expression levels, and (2) the capacity to target multiple genes simultaneously, making them suitable for enhancing complex and multigenic agronomic traits. In this mini-review, we will discuss the biogenesis, manipulation, and potential applications of plant miRNAs in improving wheat's yield, somatic embryogenesis, thermotolerance, and drought-tolerance in response to the problems of plateauing yield, genotype-dependent amenability to tissue culture, and susceptibility to climate change-induced heat and drought stress.

Human gene sequences are considered a primary source of comprehensive information about different body conditions. A wide variety of diseases including cancer, heart issues, brain issues, genetic issues, etc. can be pre-empted via efficient analysis of genomic sequences. Researchers have proposed different configurations of machine learning models for processing genomic sequences, and each of these models varies in terms of their performance & applicability characteristics. Models that use bioinspired optimizations are generally slower, but have superior incrementalperformance, while models that use one-shot learning achieve higher instantaneous accuracy but cannot be scaled for larger disease-sets. Due to such variations, it is difficult for genomic system designers to identify optimum models for their application-specific & performance-specific use cases. To overcome this issue, a detailed survey of different genomic processing models in terms of their functional nuances, application-specific advantages, deployment-specific limitations, and contextual future scopes is discussed in this text. Based on this discussion, researchers will be able to identify optimal models for their functional use cases. This text also compares the reviewed models in terms of their quantitative parameter sets, which include, the accuracy of classification, delay needed to classify large-length sequences, precision levels, scalability levels, and deployment cost, which will assist readers in selecting deployment-specific models for their contextual clinical scenarios. This text also evaluates a novel Genome Processing Efficiency Rank (GPER) for each of these models, which will allow readers to identify models with higher performance and low overheads under real-time scenarios.

Background: The species Pterodon emarginatus and P. pubescens, popularly known as white sucupira or faveira, are native to the Cerrado biome and have the potential for medicinal use and reforestation. They are sister species with evolutionary proximity. Objective: Considering that the chloroplast genome exhibits a conserved structure and genes, the analysis of its sequences can contribute to the understanding of evolutionary, phylogenetic, and diversity issues. Methods: The chloroplast genomes of P. emarginatus and P. pubescens were sequenced on the Illumina MiSeq platform. The genomes were assembled based on the de novo strategy. We performed the annotation of the genes and the repetitive regions of the genomes. The nucleotide diversity and phylogenetic relationships were analyzed using the gene sequences of these species and others of the Leguminosae family, whose genomes are available in databases. Results: The complete chloroplast genome of P. emarginatus is 159,877 bp, and that of P. pubescens is 159,873 bp. The genomes of both species have circular and quadripartite structures. A total of 127 genes were predicted in both species, including 110 single-copy genes and 17 duplicated genes in the inverted regions. 141 microsatellite regions were identified in P. emarginatus and 140 in P. pubescens. The nucleotide diversity estimates of the gene regions in twenty-one species of the Leguminosae family were 0.062 in LSC, 0.086 in SSC, and 0.036 in IR. The phylogenetic analysis demonstrated the proximity between the genera Pterodon and Dipteryx, both from the clade Dipterygeae. Ten pairs of primers with potential for the development of molecular markers were designed. Conclusion: The genetic information obtained on the chloroplast genomes of P. emarginatus and P. pubescens presented here reinforces the similarity and evolutionary proximity between these species, with a similarity percentage of 99.8%.

Background: Phosphatase and tensin homolog, widely known as PTEN, is a major negative regulator of the PI3K/AKT/mTOR signaling pathway, involved in the regulation of a variety of important cellular processes, including cell proliferation, growth, survival, and metabolism. Since most of the molecules involved in this biological pathway have been described as key regulators in cancer, the study of the corresponding genes at several levels is crucial. Objective: Although previous studies have elucidated the physiological role of PTEN under normal conditions and its involvement in carcinogenesis and cancer progression, the transcriptional profile of PTEN has been poorly investigated. Methods: In this study, instead of conducting the “gold-standard” direct RNA sequencing that fails to detect less abundant novel mRNAs due to the decreased sequencing depth, we designed and implemented a multiplexed PTEN-targeted sequencing approach that combined both short- and longread sequencing. Results: Our study has highlighted a broad spectrum of previously unknown PTEN mRNA transcripts and assessed their expression patterns in a wide range of human cancer and non-cancer cell lines, shedding light on the involvement of PTEN in cell cycle dysregulation and thus tumor development. Conclusion: The identification of the described novel PTEN splice variants could have significant implications for understanding PTEN regulation and function, and provide new insights into PTEN biology, opening new avenues for monitoring PTEN-related diseases, including cancer.

Background: The Charadriiformes provide a good source for researching evolution owing to their diverse distribution, behavior, morphology, and ecology. However, in the Charadrii, family-level relationships remain understudied, and the monophyly of Charadriidae is also a subject of controversy. Methods: In the present study, we generated complete mitogenomes for two species, Charadrius leschenaultii and Charadrius mongolus, which were found to be 16,905 bp and 16,844 bp in length, respectively. Among the 13 protein codon genes, we observed variation in the rate of nonsynonymous substitution rates, with the slowest rate found in COI and the fastest rate observed in ATP8. The Ka/Ks ratio for all Charadriidae species was significantly lower than one, which inferred that the protein-coding genes underwent purifying selection. Results: Phylogenetic analysis based on the genes of Cyt b, 12S and ND2 revealed that the genus Pluvialis is the sister group of three families (Haematopodidae, Ibidorhynchidae, Recurvirostridae). However, the phylogenetic analysis based on complete mitogenomes indicated that the genus Pluvialis is within the Charadriidae family. Conclusion: This study highlights the importance of carefully selecting the number of genes used to obtain accurate estimates of the species tree. It also suggests that relying on partial mtDNA genes with fast-evolving rates may lead to misleading results when resolving the Pluvialis sister group. Future research should focus on sequencing more mitogenomes at different taxonomic levels to gain a better understanding of the features and phylogenetic relationships within the Charadriiformes order.