Phylogenetic Analysis, Vegetative Compatibility, Virulence, and Fungal Filtrates of Leaf Curl Pathogen Colletotrichum fioriniae from Celery

Profiling Walnut Fungal Pathobiome Associated with Walnut Dieback Using Community-Targeted DNA Metabarcoding

Walnut dieback can be caused by several fungal pathogenic species, which are associated with symptoms ranging from branch dieback to fruit necrosis and blight, challenging the one pathogen-one disease concept. Therefore, an accurate and extensive description of the walnut fungal pathobiome is crucial. To this end, DNA metabarcoding represents a powerful approach provided that bioinformatic pipelines are evaluated to avoid misinterpretation. In this context, this study aimed to determine (i) the performance of five primer pairs targeting the ITS region in amplifying genera of interest and estimating their relative abundance based on mock communities and (ii) the degree of taxonomic resolution using phylogenetic trees. Furthermore, our pipelines were also applied to DNA sequences from symptomatic walnut husks and twigs. Overall, our results showed that the ITS2 region was a better barcode than ITS1 and ITS, resulting in significantly higher sensitivity and/or similarity of composition values. The ITS3/ITS4_KYO1 primer set allowed to cover a wider range of fungal diversity, compared to the other primer sets also targeting the ITS2 region, namely, GTAA and GTAAm. Adding an extraction step to the ITS2 sequence influenced both positively and negatively the taxonomic resolution at the genus and species level, depending on the primer pair considered. Taken together, these results suggested that Kyo set without ITS2 extraction was the best pipeline to assess the broadest fungal diversity, with a more accurate taxonomic assignment, in walnut organs with dieback symptoms.

A survey on the algorithm and development of multiple sequence alignment

Multiple sequence alignment (MSA) is an essential cornerstone in bioinformatics, which can reveal the potential information in biological sequences, such as function, evolution and structure. MSA is widely used in many bioinformatics scenarios, such as phylogenetic analysis, protein analysis and genomic analysis. However, MSA faces new challenges with the gradual increase in sequence scale and the increasing demand for alignment accuracy. Therefore, developing an efficient and accurate strategy for MSA has become one of the research hotspots in bioinformatics. In this work, we mainly summarize the algorithms for MSA and its applications in bioinformatics. To provide a structured and clear perspective, we systematically introduce MSA's knowledge, including background, database, metric and benchmark. Besides, we list the most common applications of MSA in the field of bioinformatics, including database searching, phylogenetic analysis, genomic analysis, metagenomic analysis and protein analysis. Furthermore, we categorize and analyze classical and state-of-the-art algorithms, divided into progressive alignment, iterative algorithm, heuristics, machine learning and divide-and-conquer. Moreover, we also discuss the challenges and opportunities of MSA in bioinformatics. Our work provides a comprehensive survey of MSA applications and their relevant algorithms. It could bring valuable insights for researchers to contribute their knowledge to MSA and relevant studies.

Bitter Rot of Apple in the Mid-Atlantic United States: Causal Species and Evaluation of the Impacts of Regional Weather Patterns and Cultivar Susceptibility

Apple growers in the Mid-Atlantic region of the United States have been reporting an increase in losses to bitter rot of apple and are requesting up-to-date management recommendations. Management is complicated by variations in apple cultivar susceptibility, temperature, rainfall, and biology of the Colletotrichum spp. that cause bitter rot. Over 500 apple fruit with bitter rot were obtained from 38 orchards across the Mid-Atlantic and the causal species were identified as Colletotrichum fioriniae and C. nymphaeae of the C. acutatum species complex and C. chrysophilum, C. noveboracense, C. siamense, C. fructicola, C. henanense, and C. gloeosporioides sensu stricto of the C. gloeosporioides species complex, the latter two being first reports. Species with faster in vitro growth rates at higher temperatures were more abundant in warmer regions of the Mid-Atlantic, while those with slower growth rates at higher temperatures were more abundant in cooler regions. Regional bloom dates are earlier and weather data show a gradual warming trend that likely influenced but was not necessarily the main cause of the recent increase in bitter rot in the region. A grower survey of apple cultivar susceptibility showed high variation, with the increase in acres planted to the highly susceptible cultivar Honeycrisp broadly corresponding to the increase in reports of bitter rot. These results form a basis for future studies on the biology and ecology of the Colletotrichum spp. responsible, and suggest that integrated bitter rot management must begin with selection of less-susceptible apple cultivars.