UNASSIGNED: The development of sequencing technology increases the number of genomes being sequenced. However, obtaining a quality genome sequence remains a challenge in genome assembly by assembling a massive number of short strings (reads) with the presence of repetitive sequences (repeats). Computer algorithms for genome assembly construct the entire genome from reads in two approaches. The de novo approach concatenates the reads based on the exact match between their suffix-prefix (overlapping). Reference-guided approach orders the reads based on their offsets in a well-known reference genome (reads alignment). The presence of repeats extends the technical ambiguity, making the algorithm unable to distinguish the reads resulting in misassembly and affecting the assembly approach accuracy. On the other hand, the massive number of reads causes a big assembly performance challenge.
UNASSIGNED: The repeat identification method was introduced for misassembly by prior identification of repetitive sequences, creating a repeat knowledge base to reduce ambiguity during the assembly process, thus enhancing the accuracy of the assembled genome. Also, hybridization between assembly approaches resulted in a lower misassembly degree with the aid of the reference genome. The assembly performance is optimized through data structure indexing and parallelization. This article\'s primary aim and contribution are to support the researchers through an extensive review to ease other researchers\' search for genome assembly studies. The study also, highlighted the most recent developments and limitations in genome assembly accuracy and performance optimization.
UNASSIGNED: Our findings show the limitations of the repeat identification methods available, which only allow to detect of specific lengths of the repeat, and may not perform well when various types of repeats are present in a genome. We also found that most of the hybrid assembly approaches, either starting with de novo or reference-guided, have some limitations in handling repetitive sequences as it is more computationally costly and time intensive. Although the hybrid approach was found to outperform individual assembly approaches, optimizing its performance remains a challenge. Also, the usage of parallelization in overlapping and reads alignment for genome assembly is yet to be fully implemented in the hybrid assembly approach.
UNASSIGNED: We suggest combining multiple repeat identification methods to enhance the accuracy of identifying the repeats as an initial step to the hybrid assembly approach and combining genome indexing with parallelization for better optimization of its performance.

The newly emerged wheat blast fungus Magnaporthe oryzae Triticum (MoT) is a severe threat to global wheat production. The fungus is a distinct, exceptionally diverse lineage of the M. oryzae, causing rice blast disease. Genome-based approaches employing MoT-specific markers are used to detect MoT field isolates. Sequencing the whole genome indicates the presence of core chromosome and mini-chromosome sequences that harbor effector genes and undergo divergent evolutionary routes. Significant genetic and pathotype diversity within the fungus population gives ample potential for evolutionary change. Identifying and refining genetic markers allows for tracking genomic regions with stable blast resistance. Introgression of quantitative and R gene resistance into popular cultivars is crucial to controlling disease in areas where the pathogen population is diverse and well established. Novel approaches such as CRISPR/Cas-9 genome editing could generate resistant varieties in wheat within a short time. This chapter provides an extensive summary of the genetic and genomic aspects of the wheat blast fungus MoT and offers an essential resource for wheat blast research in the affected areas.

SARS-CoV-2 is a new human coronavirus (CoV), which emerged in China in late 2019 and is responsible for the global COVID-19 pandemic that caused more than 97 million infections and 2 million deaths in 12 months. Understanding the origin of this virus is an important issue, and it is necessary to determine the mechanisms of viral dissemination in order to contain future epidemics. Based on phylogenetic inferences, sequence analysis and structure-function relationships of coronavirus proteins, informed by the knowledge currently available on the virus, we discuss the different scenarios on the origin-natural or synthetic-of the virus. The data currently available are not sufficient to firmly assert whether SARS-CoV2 results from a zoonotic emergence or from an accidental escape of a laboratory strain. This question needs to be solved because it has important consequences on the risk/benefit balance of our interactions with ecosystems, on intensive breeding of wild and domestic animals, on some laboratory practices and on scientific policy and biosafety regulations. Regardless of COVID-19 origin, studying the evolution of the molecular mechanisms involved in the emergence of pandemic viruses is essential to develop therapeutic and vaccine strategies and to prevent future zoonoses. This article is a translation and update of a French article published in Médecine/Sciences, August/September 2020 (10.1051/medsci/2020123).
UNASSIGNED: The online version of this article (10.1007/s10311-020-01151-1) contains supplementary material, which is available to authorized users.