Molecular Studies on the Diversity of Wild Mushrooms Indigenous to Southeastern Nigeria Using the Internal Transcribed Spacer (ITS) Region

Molecular Studies on the Diversity of Wild Mushrooms Indigenous to Southeastern Nigeria Using the Internal Transcribed Spacer (ITS) Region | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Molecular Studies on the Diversity of Wild Mushrooms Indigenous to Southeastern Nigeria Using the Internal Transcribed Spacer (ITS) Region Chidera Valentine Odo, Ngozi Eucheria Abu, Akpevwoghene Agbatutu, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9646588/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives Mushrooms are grossly under exploited and efforts to domesticate them are not yielding enough results as over 95% of mushrooms consumed in Africa and most parts of the world are still collected from the wild. However, the utility of wild mushrooms has been hampered by incorrect morphological identifications. Molecular markers including the internal transcribed spacer (ITS) region are proven to be efficient in mushroom diversity studies. This research was aimed to investigate the diversity of wild mushrooms indigenous to southeast Nigeria. Data description Fifty (50) samples of wild growing mushrooms were collected using opportunistic sampling method in 5 states of the region. Zymo Research Quick-DNA Plant/Seed Miniprep kit was used for DNA extraction, the ITS region was amplified using PCR and subsequently sequenced with sanger sequencing technology. BLASTn search in Genbank databases were conducted to determine the identity of the sampled mushrooms, while the MEGA X software was used for evolutionary analysis. Genomic DNA was successfully extracted and amplified, although with varying band quality. Forty-one (41) out of the 50 mushroom samples were successfully sequenced and identified. The identified mushroom samples were classified into 11 families with family polyporaceae (13), Agaricaceae (9), Omphatotaceae (7) and Ganodermataceae (4), topping the list. Trametes (7) and Lentinus (6) were the most abundant genera followed by Neonothopanus (5), and Ganoderma (4). The phylogeny of the ITS gene of the 41 sequenced mushrooms divided the mushroom samples into 8 major clades, although formed a polytomy with clear multifurcations. Distinct clustering of the sampled mushrooms and its Genbank relatives was observed except for the case of sample 14. Barcode marker (ITS region) was effective in diversity studies of wild mushrooms of southeastern Nigeria. Plant Molecular Biology and Genetics mushrooms DNA barcode fungal internal transcribed spacer (ITS) Zymo Figures Figure 1 Figure 2 Figure 3 INTRODUCTION In most part of Africa including Nigeria, mushrooms have become part of the diets of the common man due to their therapeutic and nutritional roles (Teke et al ., 2021). From time immemorial, most of the collections, characterization and documentations of mushroom species all over the world were based on the phenotypic traits of the fruiting bodies and preparation of cultures to distinguish between the mycelia of different mushroom species. Also, vernacular naming system and cultural traditions have been instrumental in discerning between mushroom species in some parts of the world (Tibuhwa, 2012). Although, these approaches are regularly used, they are tedious, consume time and may lack precision in differentiating interrelated species (Appiah et al ., 2017). Recently, use of biotechnological tools and molecular markers such as microsatellites, DNA barcodes and hosts of others have been introduced and adopted as the most efficient tools for species identification (Ao et al ., 2019). DNA barcoding is a reputable biotechnological tool employed by most biologists in identifying and discriminating between living organisms up to the species level (Gosavi, 2016). They are highly sophisticated and overcomes most of the challenges of the traditional methods of identification (Xu, 2016). DNA barcoding utilizes short and standardized genetic sequence of 500 to 800 bp of the target sequences to classify species of all eukaryotic taxa using the most suitable primer for each taxonomic group (Ao et al ., 2019). The use of genetic barcodes for species identification was first introduced in 2003 by Paul Hebert and colleagues who used the Cytochrome oxidase 1 (CO1) region to differentiate between butterflies (Hebert et al ., 2003). Since then, DNA barcode have been effectively utilized to classify other animal species (Young et al ., 2019), protists (Pawlowski and Lecroq, 2010), fungi (Schoch et al ., 2012; Lucking et al ., 2020) and plants (Li et al ., 2011). Apart from species identification and diversity studies, DNA barcodes have been used to checkmate fraudulently labelled foods such as fishes, meats, mushrooms as well as herbal supplements (Simmler et al ., 2015; Zhao et al ., 2021). Fungi are ranked the second most specious organism belonging to the kingdom eukaryote, but study of their diversity has suffered limitations until recently due to lack of universally accepted DNA barcode marker (Khaund and Joshi, 2014). Finding an effective and broadly suitable barcode or molecular markers for fungal species identifications was tedious but recently a multinational collaborative consortium of mycologists endorsed the Internal Transcribed Spacer (ITS) area as the most suitable barcode marker for fungi identification and classification (Schoch et al ., 2012). The choice of ITS over other notable nuclear barcode markers such as small subunits (nSSU), large subunits (nLSU) and other protein-coding genes such as the largest subunit of RNA polymerase II (RPBI), second largest subunit of RNA polymerase II (RPB2) and minichromosome maintenance protein (MCM7) was probably due to its wide acceptability and efficiency in diversity studies of over seventeen (17) fungal families which include the Basidiomycota and Ascomycota that are the largest phyla in the fungal kingdom (Xu, 2016; Raja et al ., 2017). Southeast Nigeria is one of the major regions of Nigeria endowed with natural and wild growing mushrooms that are capable of bridging the nutritional gaps of the staple crops. Unfortunately, inconsistencies in morphological identifications and phobia of consuming poisonous mushroom species have resulted to gross negligence of mushrooms in the region. Lately, the use of biotechnological tools in species identifications has proven to be more precise and reliable. The use of DNA barcodes in fungal identifications have been reported by some authors in so many countries (Geiser et al . 2007; Seena, et al ., 2010; Robideau et al ., 2011; Khaund and Joshi, 2014; Khodadadi et al ., 2014; Elwess et al ., 2016; Irinyi et al ., 2016). In Nigeria, the use of biotechnological tools such as barcode markers for mushroom diversity studies have not been properly harnessed. Very few diversity studies of mushrooms using DNA barcode in Nigeria have been reported; Adedokun et al . (2016) who characterized the mushrooms of Niger Delta region of Nigeria and Adeniyi et al . (2018) and Adebayo et al . (2021) that worked in the western region of Nigeria, hence the need to investigate mushroom diversity in other regions of Nigeria such as Southeast which rely greatly on mushrooms as alternative for other expensive source of proteins and dietary nutrients. MATERIALS AND METHODS Study location Southeast is one of the six (6) geopolitical zones of Nigeria which comprises five (5) states (Abia, Anambra, Ebonyi, Enugu and Imo) (Figure 1) out of the thirty six (36) states including Abuja, the federal capital territory (Anejionu et al ., 2013). The region is located within longitudes 6 0 E to 8 0 E and latitudes 5 0 N and 6 0 N (Osugiri et al ., 2019), with an estimated population of 16,395,554 and a land mass of 10,952,400 hectares (Ibe et al ., 2022). Southeast Nigeria predominantly belongs to the tropical rainforest zone, although the vegetation stretches from the derived savannah in the interior to the mangrove swamp in the coast (Okoroafor et al ., 2017). Distinguishing between the rainy and dry seasons are challenging, although rainy and dry seasons are more pronounced between May to October and November to April respectively. The region has an annual mean temperature of 28 0 C and annual rainfall of 2000 to 3000 mm (Osugiri et al ., 2019). People of southeast Nigeria are mostly the Igbo speaking tribe with unique culture and practice subsistence level of Agriculture under rain-fed conditions. Sample collection and preservation Fifty (50) mushrooms samples were collected randomly from various locations in the five (5) states of Southeastern Nigeria using the opportunistic method of sampling macrofungi or mushroom diversity (Lodge et al ., 2004; Prayudi et al ., 2019). Photographs of each mushroom sample were taken in situ before harvesting. They were harvested and put into separate paper bags and labelled properly. All the collected mushroom samples were transported to the department of Plant Science and Biotechnology and were oven-dried for 2 days at 50 0 C before taken to the Biotechnology Laboratory of the department of Biological Sciences, Godfrey Okoye University, Enugu for DNA extraction, gel electrophoresis, polymerase chain reaction. List of sampled mushrooms, date of collection, locality, state and their habitats are presented in Table 1. Table 1: Lists of samples and their habitats, date of collection, town, local government and state of collection Samples Date of collection Town LGA State Substrate/Habitat S1 23/5/2023 Imilike-Agu Udenu Enugu Soil S2 23/5/2023 Botanic Garden UNN Nsukka Enugu Dead Tree Stump S3 25/5/2023 Isuochi Umunneochi Abia Soil S4 25/5/2023 Isuochi Umunneochi Abia Soil S5 25/5/2023 Iheakpu-Awka Igbo-Eze South Enugu Soil S6 25/5/2023 Uhunowerre Igbo-Eze South Enugu Dead Tree Stump S7 30/5/2023 Arondiokoroji Okigwe Imo Dead Tree Stump S8 30/5/2023 Arondiokoroji Okigwe Imo Soil S9 30/5/2023 Isuochi Umunneochi Abia Dead Wood S10 30/5/2023 Arondiokoroji Okigwe Imo Soil S11 1/6/2023 Uvuru Uzo-Uwani Enugu Soil S12 1/6/2023 Amube Igbo-Eze North Enugu Dead Palm Tree S13 3/6/2023 Okoji Ula-Ekwulobia Aguata Anambra Dead Wood S14 3/6/2023 Okoji Ula-Ekwulobia Aguata Anambra Dead Wood S15 3/6/2023 Nkwelle –Ezunaka Oyi Anambra Dead Wood S16 3/6/2023 Nkwelle –Ezunaka Oyi Anambra Soil S17 3/6/2023 Nkwelle –Ezunaka Oyi Anambra Soil S18 5/6/2023 Unadu Igbo-Eze South Enugu Dead wood S19 5/6/2023 Iwollo Ezeagu Enugu Soil S20 6/6/2023 Oboro Ikwuano Abia Soil S21 6/6/2023 Oboro Ikwuano Abia Soil S22 6/6/2023 Okoji Ula-Ekwulobia Aguata Anambra Dead Wood S23 8/6/2023 Umuduru Isiala Mbano Imo Soil S24 8/6/2023 Ibagwa-Aka Igbo-Eze South Enugu Dead Tree Stump S25 9/6/2023 Uturu Isuikwuato Abia Dead Wood S26 9/6/2023 Uturu Isuikwuato Abia Dead Wood S27 4/7/2023 Aguleri Anambra North Anambra Soil S28 5/7/2023 Umuduru Isiala Mbano Imo Dead Wood S29 5/7/2023 Umuduru Isiala Mbano Imo Dead Wood S30 5/7/2023 Awba-Ofemili Awka North Anambra Decaying Wood S31 12/7/2023 Uturu Isuikwuato Abia Dead Tree Branch S32 12/7/2023 Obollo-Afor Udenu Enugu Soil S33 12/7/2023 Aguleri Anambra North Anambra Dead Tree Stump S34 12/7/2023 Aguleri Anambra North Anambra Dead Palm Log S35 18/7/2023 Amufie Igbo-Eze North Enugu Tree Stump S36 18/7/2023 Umuduru Isiala Mbano Imo Dead Wood S37 23/7/2023 PG Hostel UNN Nsukka Enugu Soil S38 23/7/2023 Okata Igbo-Eze North Enugu Soil S39 23/7/2023 Obukpa Nsukka Enugu Dead Mango Wood S40 28/7/2023 Oboro Ikwuano Abia Dead Wood S41 29/7/2023 Awba-Ofemili Awka North Anambra Dead Palm Wood S42 29/7/2023 Ndufu-Aliki Ikwo Ikwo Ebonyi Dead Tree Trunk S43 29/7/2023 Akokwa Ideato North Imo Dead Wood S44 29/7/2023 Akokwa Ideato North Imo Dead Wood S45 29/7/2023 PG Hostel UNN Nsukka Enugu Soil S46 7/8/2023 Aguleri Anambra North Anambra Dead Wood S47 7/8/2023 Awba-Ofemili Awka-North Anambra Soil S48 7/8/2023 Iheakpu-Awka Igbo-Eze South Enugu Soil S49 7/8/2023 Iheakpu-Awka Igbo-Eze South Enugu Soil S50 7/8/2023 Awba-Ofemili Awka-North Anambra Dead Wood DNA extraction Following the methodology of Adedokun et al . (2016) the oven dried mushroom fruiting bodies were crushed into powder with the help of liquid nitrogen. Genomic DNA extraction was done using Zymo Research Quick-DNA Plant/Seed Miniprep kit (cat. D6020) following the manufacturers procedures. The quality of the extracted DNA was determined using 1% agarose gel electrophoresis. PCR amplification and sequencing The methodology and procedures of Cold Spring Harbor Laboratory (2014) was adopted. The internal transcribed spacer (ITS) regions ( ̴ 600 bp) of rRNA gene were amplified with ITS-5 forward (5´- GGA AGT AAA AGT CGT AAC AAG G - 3´) and ITS-4 reverse (5´- TCC TCC GCT TAT TGA TAT GC - 3´) primers according to White et al . (1990) and Adedokun et al . (2016). The primers were synthesized in a DNA synthesizer (Applied Biosystems, UK) at Inqaba Biotec Company, Pretoria (South Africa). PCR was carried out in a total volume of 25µl containing 2.0 µl of genomic DNA, 12.5 µl of 1 x PCR master mix (New England Biolabs, New York, NY, USA), 1.0 µl each of forward and reverse primer (10 mM) and 8.5 µl of H 2 O. The PCR products were viewed using 1% Agarose gel and Sybr green dye. The PCR was run at 100 v for 30 minutes. Amplifications were done in a thermal cycler with an initial denaturation step of 94 o C for 3 minutes and followed by another 30 cycles of denaturation step at 90 o C, annealing at 56 o C and elongation for 72 o C at 1 minute each. The final extension was done at 72 o C for 10 minutes. The PCR products were sequenced at Inqaba Biotec Company, Pretoria, South Africa to obtain the nucleotide sequence of the DNA barcodes of the different mushroom samples. Three (3 μl) of the samples were diluted with 1 μl of primer and 3 μl milliq water before sequencing. Sequence analysis software v 6.2 from Thermos Fisher Inc were used to analyze the sequence (Adebayo et al ., 2021). Phylogenetic analysis of ITS region The sequences were edited by trimming and assembling to obtain a consensus sequence data using the CLC work bench 6.9.1. (Adedokun et al ., 2016). Each of the nucleotide sequence was compared with the nucleotide sequence in the National Center for Biotechnology Information (NCBI), DNA Subway, Barcode of Life Database (BOLD) and UNITE databases using the Basic Local Alignment Search Tool (BLAST) to check for highest percentage identity score or the Lowest Expectation of E-value. The evolutionary history among different mushroom species was inferred using the Neighbor Joining method (Saitou and Nei, 1987). The bootstrap consensus tree inferred from 1000 replicates (Felsenstein, 1985 ) is taken to represent the evolutionary history of the taxa analyzed. Branches corresponding to partitions reproduced in less than 50% bootstrap replicates are collapsed. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) are shown next to the branches. The evolutionary distances were computed using the p-distance method (Nei and Kumar, 2000) and are in the units of the number of base differences per site. The analysis involved 42 nucleotide sequences. All positions containing gaps and missing data were eliminated (complete deletion option). There was a total of 162 positions in the final dataset. Evolutionary analyses were conducted in MEGA X (Kumar et al ., 2018). Aspergillus niger served as the outgroup. The purpose of including an outgroup is to establish the ancestral (basal) position in relation to the other taxa being analyzed. The outgroup provides insight into the evolutionary relationships among the taxa of interest. It serves as a reference point for determining ancestral and derived traits and rooting the tree to show the direction of evolutionary change. RESULTS AND DISCUSSIONS A total of 50 mushroom samples were collected from the 5 southeastern states of Nigeria (Table 1). Nine (9) mushroom samples were collected from 3 different local government areas in Abia State, while fourteen (14) samples were collected from 4 local government areas in Anambra State. In Ebonyi state, sample was collected from only one local government area. However, in Enugu state, 17 mushroom samples were collected from 6 different local government areas, while, 9 mushroom samples were collected from 3 different local government areas in Imo state. There were two (2) groups of mushroom samples based on the substrates they grew on. Twenty-nine (29) out of the 50 samples were found to grow on dead decaying woods, while the remaining 21 samples grow on the soil. Distribution of mushroom species as shown in this research is an indication of the prolific growth and development of wild mushrooms in Southeast Nigeria. Effective sampling of mushroom species between late May and early August was possible due to the boom in mushroom growth and development within the period. However, this boom may be connected to heavy rainfall and high humidity usually encountered in this zone during this period, since mushrooms with suitable substrates are known to flourish in areas with high humidity and rainfall. Previous researchers have demonstrated that mushrooms thrive exceptionally well in regions with high rainfall and humidity (Markson et al ., 2017; Adeniyi et al ., 2018; Titilawo et al ., 2022). Greater number of the sampled mushrooms were observed to grow on decaying logs of wood, while the remaining samples grew on soil and dead organic matter. The preference of dead decaying woods as substrates may be due to high lignocellulosic compounds in woods which are known to support macrofungi growth and development. Earlier researchers have shown that mushroom species flourish on a variety of substrates but prefer lignin, cellulose and organic matter rich substrates (Titilawo et al ., 2022). Agarose gel electrophoresis 1 % (w/v) analysis on the presence and quality of extracted genomic DNA showed and confirmed the presence of genomic DNA molecules from the mushroom samples, although with band quality ranging from sharp to very faint. Variations in the quality of DNA extracted from the sampled mushrooms as revealed by the bands in the agarose gel pictures is an indication that, DNA were successfully extracted, but their quality may have been influenced by factors such as adopted protocol, technicalities and type of organism. Earlier report has shown that varied organism, genotype and even cultivars may respond differently to DNA extraction protocols (Ganiyu et al ., 2017). The PCR products of the ITS gene (900 – 1000 bp) loaded in agarose gel 1 % (w/v) and viewed using high-performance UV transilluminator showed conspicuous bands in all the amplified samples except in only few cases that showed faint bands. Bands of the PCR products as was revealed by the agarose gel pictures is a clear-cut sign that the ITS region (900 – 1000 bp) was successfully amplified. However, the quality of the bands varied across the samples and this may be ascribed to the differences in genetic backgrounds and the resulting wide variations in bioactive compositions of the sampled mushrooms. Studies before now have demonstrated that, abundance of bioactive compounds such as polyphenols, polysaccharides and tannin influence the oxidation and degradation of DNA, resulting in the failure of PCR (Arruda et al ., 2017). The BLAST results from DNA subway, NCBI, BOLD and UNITE as depicted in Table 2 identified most of the mushroom samples. Over a quarter of the sampled mushrooms (S4, S7, S12, S15, S18, S25, S32, S36, S38, S39, S43, S44, S46 and S47) had similar identifications up to the species level using the four databases. Moreover, some of the mushroom samples were identified by the four databases to belong to the same genus but varied in their species identifications. For instance, while the DNA subway, NCBI and UNITE databases identified sample 1 as Amanita nauseosa , the BOLD identified the sample as Amanita manicata . Similar trend was observed in samples 2, 6, 8, 9, 14, 17, 22, 24, 27, 28, 30, 31, 33, 35, 37 and 42 (Table 2). In other samples, the four databases lacked consistency in identifying the genus of the samples. For example, sample 5 was identified as Marasmiellus sp. by the DNA subway, NCBI and BOLD databases, while the UNITE database identified it as Campanella junghuhnii . This was also observed in samples 10, 20, 23, 26, 31, 35, 40, 41 and 50 (Table 2). However, sample 14 could not be identified using the DNA subway. Sample 16 was identified as an uncultured fungus by both the DNA subway and the NCBI, while the BOLD and UNITE identified it as Ganoderma lucidum. The efficiency of NCBI database in identifying most of the mushroom samples up to the species level could be linked to its wide applications and coverage. While the NCBI serves as a general database for all organism irrespective of sequence region, the DNA subway is a subset of the NCBI with limited data. The BOLD and UNITE databases focus more on the fungi and ITS region respectively, which may possibly limit their utility in fungi identifications (Raja et al ., 2017). Nevertheless, molecular identification of organisms in more than one database could be helpful in authenticating the identity of an organism. This observation explains the reason why NCBI database have been used in molecular identifications of virtually all organisms. Precise identifications of mushrooms will clarify the uncertainties surrounding their usage in drug development and formulation of nutritional supplements. According to Adeniyi et al . (2018), correct taxonomical identification of any organism is fundamental and germane to their use in further studies. Successful identification of the sampled mushrooms using their ITS region confirms its efficacy in molecular characterization of mushrooms. This agrees with Schoch et al . (2012), which confirmed the ITS region as the most potent and effective barcode marker for molecular identifications of fungi. Although, the BLAST results showed some consistency in identification of some mushroom samples across different databases, others were not consistent. However, the discrepancies may be connected to the inconsistencies in submission of sequences in databases, since close to 27% of fungal ITS sequences submitted in the databases are insufficiently identified taxonomically (Nilsson et al ., 2006; Raja et al ., 2017). More so, it is estimated that approximately 20% of the fungal sequences in the databases may be incorrectly annotated, although they may differ greatly based on taxonomic groups (Raja et al ., 2017). Similarity percentage of most of our sampled mushroom sequences and its Genbank relatives are less than 100% and Oyetayo (2014) suggested that this situation could be linked to variations in ecological zones. The query length of the identified mushroom species ranged from 395 – 770 as found in sample 18 and 50 respectively. However, the percentage identity score of the mushroom samples ranged from 71.23 – 100. More so, it is worthy to note that all the identified mushroom species had an E-value of 0.00 except for the cases of sample 16, 18, 21 and 23 that had higher E-values (Table 2). The accession numbers and all the associated information of all the identified mushrooms are presented in Table 2. The families of the sampled mushrooms as represented in Table 3 divided all the 41 identified mushrooms into 11 families; polyporaceae (13) representing 31.707% of the identified mushrooms and Agaricaceae (9) which represented 21.951% of the identified mushrooms. Family Omphatotaceae had 7 mushrooms samples and represented 17.073% of the identified mushroom samples. Family Ganodermataceae and Marasmiaceae had 4 and 2 samples, respectively which represented 9.756% and 4. 878% of the entire identified mushrooms. Other, families such as Amanitaceae, Auriculariaceae, Russulaceae, Hypoxylaceae, Physalacriaceae and Bondarwiaceae had 1 mushroom each which represented 2.439% each of the entire identified mushrooms. Greater number of mushrooms samples belonging to the family Polyporaceae recorded in this study signifies their abundance in the region. Their abundance in the region may be associated with their versatility in the choice of substrates and ability to thrive in the prevailing environmental conditions. Similar trend was reported in the wild mushrooms of Niger Delta of Nigeria, where family Polyporaceae had the highest number of samples (40.4%) of all the sampled mushrooms (Adedokun et al ., 2016). More so, Apollos et al . (2017) worked on the molecular characterization of mushrooms in Kogi State and reported that Polyporaceae accounted for majority of the sampled mushrooms (60%). Elsewhere, Appiah et al . (2017) reported that Polyporaceae was the most abundant (33.33%) in some Ghana mushrooms. Molecular characterization of 56 mushrooms sampled at Adirondack Park had family Russulaceae (12.5%) as the most abundant and family Polyporaceae (8.93%) as the second most abundant (Elwess et al ., 2016). In sharp contrast to the findings of this study, Adeniyi et al . (2018) reported family Tricholomataceae (52.63%) as the most abundant while Polyporaceae family was not recorded in some wild mushrooms of Nigeria. The differences may be attributed to the sampling methods adopted or the time of sampling, since they share to some extent similar environmental conditions. Identifications of Mushroom species belonging to families such as Agaricaceae and Omphatotaceae that ranked second and third, respectively indicate that large numbers could be found in the region if the number of samples are increased. More so, mushroom families such as Ganodermataceae, Marasmiaceae, Amanitaceae, Auriculariaceae, Russulaceae, Hypoxylaceae, Physalacriaceae and Bondarwiaceae found in varying amounts confirms their presence and indicate that more representative species may be found in the region with a more intense sampling. A total of 11 different families recorded in this study differ from 19 families reported by Elwess et al . (2016), 13 families by Adedokun et al . (2016), 5 families by Apollos et al . (2017) and 4 families by Adeniyi et al . (2018). However, since the number of samples studied by each author varied, it will be reasonable to suggest that variations in the number of families may have a direct link with the number of samples studied The 41 identified mushrooms were classified into 17 different genera with Trametes (7) being the most abundant and followed by Lentinus (6). They were followed by other genera such as Neonothopanus (5), Ganoderma (4), Leucocoprinus (3), Chlorophyllum (3). Genera such as Agaricus and Marasmius had 2 samples each, while genera such as Auricularia, Microsalliota, Daldinia, Oudemansiella, Amanita, Amylosporus, Lactifluus, Marasmiellus and Gumnopus had 1 sample each. More so, the sampled mushrooms were classified into 19 different species with 5 genera which could not be identified up to the species level. Trametes was evidently the most abundant genus found in this study and was followed by Lentinus spp . Although Lentinus squarrosulus was not the most abundant sampled genus, they were remarkably high and compared favourably with the report of Adedokun et al . (2016) that reported them as the most abundant sampled mushrooms with 19 samples. The finding is evidence that Trametes spp and Lentinus squarrosulus may be highly distributed in Nigeria especially within the tropical and derived savannah vegetation zones. The edibility status of the sampled mushrooms was computed using reliable reference articles (Table 3). In line with the articles, we were able to characterize our samples into edible, non-edible and unknown categories. Twenty-eight (28) samples which represent 68.293% of the 41 identified mushrooms are edible. Eleven (11) samples which represent 26.829% of the identified mushrooms are non-edible, while 2 samples (4.878%) have unknown edibility status. The edible status of majority of the sampled mushrooms indicates that the region is endowed with mushroom species that can be consumed for nutritional and medicinal purposes. Distinguishing between edible and non-edible mushrooms have been based on traditional knowledge, folk tales and in recent times chemical analysis. Unfortunately, these methods are not reliable and may expose one to poisoning if the wrong species are consumed. Nevertheless, efforts are now geared towards discerning between edible and non-edible species through molecular identifications. These molecular identifications could encourage mushroom foraging and enable the populace harness the full potentials of these mushrooms in diets and medicines. More so, important constituents which can be used in drug and supplement formulations can be extracted from non-edible species. Phylogram showing the evolutionary relatedness of the sampled mushrooms disclosed they clustered distinctly (Figure 2). Sample 14 ITS which was closely identified as Trametes polyzona is a basal taxon and it indicates that the taxa/species has the ability to remain relatively unchanged and has maintained most ancestral traits overtime or may have not undergone significant evolutionary modifications. Although, 14 ITS was closely identified as samples 28 ITS, 33 ITS and, 26 ITS to the species level ( Trametes polyzona ) and identified to belong to the same genera as 31 ITS, 35 ITS and 40 ITS ( Trametes parvispora ), they were not classified in the same clade due to evolutionary distance. The distinct clustering suggests that the species have relatively large genetic or evolutionary distances between them. While samples 28 ITS, 33 ITS and, 26 ITS each had about 99.8% identity with Trametes polyzona, sample 14 ITS had just 85% identity to its closest Genbank relative, Trametes polyzona. However, samples 28 ITS, 33 ITS and, 26 ITS do not belong to the same species, but are more related to 31 ITS, 35 ITS and 40 ITS than they are to 14 ITS. Group of mushroom species, (28 ITS, 33 ITS, 26 ITS) which formed a polytomy including the subsequent listed groups of mushroom species (31 ITS, 35 ITS, 40 ITS), (41 ITS, 25 ITS, 20 ITS), (17 ITS, 27 ITS, 37 ITS), (12 ITS, 4 ITS, 25 ITS), (8 ITS, 22 ITS, 30 ITS), clearly revealed multifurcation which could be as a result of insufficient genetic or morphological data to determine the exact evolutionary changes. The multifurcation could also be due to complexity of evolutionary history or uncertainty about the relationships among the taxa. The species in each of the listed groups, (43 ITS and 46 ITS), (15 ITS and18 ITS), (28 ITS and 33B ITS), (35 ITS and 40 ITS), (21 ITS and 24 ITS), (16A ITS and 21A ITS), (4 ITS and 25 ITS), (32 ITS and 47 ITS), (27 ITS and 37 ITS), (39 ITS and 44 ITS), (5 ITS and 41 ITS), (6 ITS and 42 ITS) are sister taxa, which signifies that they share a more recent common ancestor with each other than with any other taxa in the tree. These groups of taxa, (43 ITS and 46 ITS), (15 ITS and18 ITS), (28 ITS and 33 ITS), (35 ITS and 40 ITS), (21 ITS and 24 ITS), (16 ITS and 21 ITS), (4 ITS and 25 ITS), (32 ITS and 47 ITS), (27 ITS and 37 ITS), (39 ITS and 44 ITS), (5 ITS and 41 ITS), (6 ITS and 42 ITS) together with their common ancestor (node) formed a monophyletic group which show they have a common ancestral population. Distinct clustering of the sampled mushroom species in this study and its Genbank relatives indicates the novelty of the collected mushroom species as none of the samples except 14 ITS formed a clade with their closest Genbank relatives (Figure 3). The distinct separation clearly indicates the need for further studies on the sampled mushroom species. Similar finding was made by Adeniyi et al . (2018), where they observed distinct clustering of the sampled mushroom with the reference Genbank relatives and suggested disparity in nucleotide signature may be responsible. Aremu and Babalola (2015) also stated that differences in nucleotide compositions could amount to distinct clustering of species with its Genbank relatives. CONCLUSIONS Notwithstanding the widespread developments, urbanization and climate change that has grossly affected biodiversity, wild mushrooms were still found in substantial amounts in Southeast Nigeria. However, the isolated mushrooms varied widely within families, genera and even species. Successful extraction of DNA from the sampled mushrooms using Zymo Research Quick-DNA Plant/Seed Miniprep kit confirm its extraction potency, while the amplification successes of the ITS region using the PCR indicate high amplification rate of the region. Sequencing rate of 82% recorded could be ascribed to quality of the amplified DNA and not due to sequencing failures. The BLAST reports shows that the ITS region was very effective in identifying the sampled mushrooms up to the species level. Highest number of mushrooms samples belonging to Polyporaceae family suggest they are the most distributed mushroom family in the region. Out of the identified mushroom samples, Trametes spp and Lentinus squarrosulus were very abundant in the region, while other species such as Ganoderma spp , Neonothopanus spp , Chlorophyllum spp and so on were also found in good quantities. Nonetheless, with more intense sampling, a greater number of mushroom species belonging to different families may be encountered. The evolutionary relationship of the sampled mushrooms as depicted by the phylogram showed they had distinctive ancestral lineages. Apart from 14 ITS that clustered differently with its closest relatives, other closely related species clustered and formed unique clades that shared similar ancestral lineages. The distinctive clustering of the sampled mushrooms and their Genbank relatives indicates the novelty of the sampled mushrooms and the need for more studies on the diversity of mushrooms in southeast Nigeria using molecular identifications. Table 2: Depicts the Sequence source organism (top hit), Percentage Identity, Query Coverage, Total Score and Accession number S/N Query Length Sequenced Source Organisms (Top Hit) DNA SUBWAY Sequenced Source Organisms (Top Hit) NCBI BOLD UNITE Percentage Identity (%) Query Cover (%) E-value Accession Number 1 672 Amanita nauseosa Amanita nauseosa Amanita manicata Amanita nauseosa 99.26 100 0.0 HQ625013.1 2 572 Ganoderma mbrekobenum Ganoderma mbrekobenum Ganoderma applanatum Ganoderma applanatum 100 100 0.0 KX000898.1 4 677 Leucocoprinus cepistipes Leucocoprinus cepistipes Leucocoprinus cepistipes Leucocoprinus cepistipes 98.33 100 0.0 MK412593.1 5 584 Marasmiellus sp. Marasmiellus sp. Marasmiellus sp. Campanella junghuhnii 95.38 100 0.0 MK167361.1 6 605 Neonothopanus sp. Neonothopanus hygrophanus Neonothopanus sp Neonothopanus nambi 98.68 100 0.0 MW298684.1 7 607 Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus 100 100 0.0 KT120037.1 8 588 Neonothopanus hygrophanus Neonothopanus hygrophanus Neonothopanus sp. Neonothopanus nambi 98.3 100 0.0 MK931357.1 9 542 Auricularia polytricha Auricularia polytricha Auriculariaauricula-judae Auricularia cornea 99.26 100 0.0 KT273351.1 10 671 Marasmius corrugatiformis Marasmius corrugatiformis Pouzarella dysthales Marasmius pellucidus 93.89 99 0.0 KX953757.1 S/N Query Length Sequenced Source Organisms (Top Hit) DNA SUBWAY Sequenced Source Organisms (Top Hit) NCBI BOLD UNITE Percentage Identity (%) Query Cover (%) E-value Accession Number 12 629 Leucocoprinus cretaceous Leucocoprinus cretaceous Leucocoprinus cretaceous Leucocoprinus cretaceous 99.52 100 0.0 MN483022.1 14 694 Null Trametes polyzona Trametes polyzona Trametes sanguinea 85.24 94 0.0 OL685335.1 15 414 Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus 94.63 93 0.0 KT120055.1 16 499 Uncultured fungus Uncultured fungus Ganoderma lucidum Ganoderma lucidum 85.06 100 2.79-83 LR993654.1 17 686 Chlorophyllum palaeotropicum Chlorophyllum palaeotropicum Chlorophyllum molybdites Chlorophyllum palaeotropicum 94.94 100 0.0 MN318425.1 18 395 Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus 87.41 98 3e-156 KT120055.1 19 PS PS PS PS PS PS PS PS PS 20 622 Micropsalliota sp. Micropsalliota sp. Micropsalliota globocystis Lycoperdaceae sp. 90.71 100 0.0 OM397374.1 S/N Query Length Sequenced Source Organisms (Top Hit) DNA SUBWAY Sequenced Source Organisms (Top Hit) NCBI BOLD UNITE Percentage Identity (%) Query Cover (%) E-value Accession Number 21 573 Ganodrma sp. Ganodrma sp. Ganoderma lucidum Ganoderma lucidum 97.82 100 1.94E-93 KT120034.1 22 567 Neonothopanus hygrophanus Neonothopanus hygrophanus Neonothopanus sp. Neonothopanus nambi 98.59 100 0.0 MK931357.1 23 611 Lactifluus bicapillus Lactifluus bicapillus Lactarius rubroviolascens Lactifluus sp. 71.23 71 8e-127 MH549203.1 24 583 Ganoderma mbrekobenum Ganoderma mbrekobenum Ganoderma applanatum Ganoderma applanatum 95.44 100 0.0 KX000898.1 25 675 Leucocoprinus cepistipes Leucocoprinus cepistipes Leucocoprinus cepistipes Leucocoprinus cepistipes 98.33 100 0.0 MK412593.1 26 517 Trametes polyzona Trametes polyzona Trametes polyzona Lenzites sp 99.42 100 0.0 MH855813.1 27 703 Chlorophyllus globosum Chlorophyllus globosum Chlorophyllum globosum Chlorophyllum molybdites 99.71 100 0.0 MH287459.1 28 564 Trametes polyzona Trametes polyzona Trametes polyzona Trametes hirsute 99.46 100 0.0 MH131681.1 29 PS PS PS PS PS PS PS PS PS S/N Query Length Sequenced Source Organisms (Top Hit) DNA SUBWAY Sequenced Source Organisms (Top Hit) NCBI BOLD UNITE Percentage Identity (%) Query Cover (%) E-value Accession Number 30 582 Neonothopanus hygrophanus Neonothopanus hygrophanus Neonothopanus sp. Neonothopanus nambi 98.78 99 0.0 MK931357.1 31 561 Trametes parvispora Trametes parvispora Trametes meyenii Lenzites warnieri 99.11 100 0.0 MK736990.1 32 612 Agaricus sp. Agaricus sp. Agaricus sp. Agaricus sp. 96.25 100 0.0 KJ540956.1 33 556 Trametes polyzona Trametes polyzona Trametes polyzona Trametes hirsute 99.45 100 0.0 MH131681.1 35 564 Trametes parvispora Trametes parvispora Trametes meyenii Lenzites warnieri 99.29 99 0.0 MK736990.1 36 623 Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus 100 100 0.0 KT273380.1 37 577 Chlorophyllum globosum Chlorophyllum globosum Chlorophyllum globosum Chlorophyllum molybdites 99.65 100 0.0 KJ524553.1 38 678 Gymnopus aff. Brunneigracilis Gymnopus aff. Brunneigracilis Gymnopus brunneigracilis Gymnopus sp. 97.8 100 0.0 MF100983.1 39 506 Daldinia eschscholtzii Daldinia eschscholtzii Daldinia eschscholtzii Daldinia eschscholtzii 99.8 100 0.0 MT507855.1 S/N Query Length Sequenced Source Organisms (Top Hit) DNA SUBWAY Sequenced Source Organisms (Top Hit) NCBI BOLD UNITE Percentage Identity (%) Query Cover (%) E-value Accession Number 40 563 Trametes parvispora Trametes parvispora Trametes meyenii Lenzites warnieri 99.47 100 00 MK736990.1 41 659 Marasmius palmivorus Marasmius palmivorus Marasmius sp Campanella junghuhnii 96.84 100 0.0 MH131681.1 42 692 Neonothopanus hygrophanus Neonothopanus hygrophanus Neonothopanus sp. Neonothopanus nambi 99.13 99 0.0 MK931357.1 43 620 Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus 99.84 100 0.0 MH172168.1 44 733 Oudemansiella canarii Oudemansiella canarii Oudemansiella canarii Oudemansiella sp. 98.48 99 0.0 AY216473.1 46 598 Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus Lentinus squarrosulus 100 100 0.0 MH172168.1 47 672 Agaricus sp. Agaricus sp. Agaricus sp. Agaricus sp. 96.88 100 0.0 KJ540956.1 50 770 Amylosporus sp. Amylosporus campbellii Amylosporus campbellii Scytinostromella nannfeldtii 97.81 100 0.0 ON033917.1 KEY: PS = Poor Sequence Table 3: Summarized table showing mushroom identification, family and edibility status Sample Number Identified Mushrooms Family Edibility Status References 1 Amanita nauseosa Amanitaceae Unknown 2 Ganoderma mbrekobenum Ganodermataceae Non-edible Hapuarachchi et al . (2018) 4 Leucocoprinus cepistipes Agaricaceae Edible Bastos et al . (2023) 5 Marasmiellus sp. Omphatotaceae Edible Bastos et al . (2023) 6 Neonothopanus hygrophanus Omphatotaceae Edible Bastos et al . (2023) 7 Lentinus squarrosulus Polyporaceae Edible Li et al . (2021), Ishaq et al . (2022), Bastos et al . (2023) 8 Neonothopanus hygrophanus Omphatotaceae Edible Bastos et al . (2023) 9 Auricularia polytricha Auriculariaceae Edible Li et al . (2021) 10 Marasmius corrugatiformis Marasmiaceae Edible Li et al . (2021), Bastos et al . (2023) 12 Leucocoprinus cretaceous Agaricaceae Edible Bastos et al . (2023) 14 Trametes polyzona Polyporaceae Non-edible Li et al . (2021) 15 Lentinus squarrosulus Polyporaceae Edible Li et al . (2021), Ishaq et al . (2022), Bastos et al . (2023) 16 Ganoderma lucidum Ganodermataceae Non-edible Hapuarachchi et al . (2018) 17 Chlorophyllum palaeotropicum Agaricaceae Edible Bastos et al . (2023) 18 Lentinus squarrosulus Polyporaceae Edible Li et al . (2021), Ishaq et al . (2022), Bastos et al . (2023) 20 Micropsalliota sp. Agaricaceae Edible Bastos et al . (2023) 21 Ganodrma sp. Ganodermataceae Non-edible Hapuarachchi et al . (2018) 22 Neonothopanus hygrophanus Omphatotaceae Edible Bastos et al . (2023) 23 Lactifluus bicapillus Russulaceae Edible Bastos et al . (2023) 24 Ganoderma mbrekobenum Ganodermataceae Non-edible Hapuarachchi et al . (2018) 25 Leucocoprinus cepistipes Agaricaceae Edible Bastos et al . (2023) 26 Trametes polyzona Polyporaceae Non-edible Li et al . (2021) 27 Chlorophyllus globosum Agaricaceae Edible Bastos et al . (2023) 28 Trametes polyzona Polyporaceae Non-edible Li et al . (2021) 30 Neonothopanus hygrophanus Omphatotaceae Edible Bastos et al . (2023) 31 Trametes parvispora Polyporaceae Non-edible Li et al . (2021) 32 Agaricus sp. Agaricaceae Edible Li et al . (2021) 33 Trametes polyzona Polyporaceae Non-edible Li et al . (2021) 35 Trametes parvispora Polyporaceae Non-edible Li et al . (2021) 36 Lentinus squarrosulus Polyporaceae Edible Li et al . (2021), Ishaq et al . (2022), Bastos et al . (2023) 37 Chlorophyllum globosum Agaricaceae Edible Bastos et al . (2023) 38 Gymnopus aff. Brunneigracilis Omphalotaceae Edible Li et al . (2021) 39 Daldinia eschscholtzii Hypoxylaceae Unknown 40 Trametes parvispora Polyporaceae Non-edible Li et al . (2021) 41 Marasmius palmivorus Marasmiaceae Edible Li et al . (2021), Bastos et al . (2023) 42 Neonothopanus hygrophanus Omphatotaceae Edible Bastos et al . (2023) 43 Lentinus squarrosulus Polyporaceae Edible Li et al . (2021), Ishaq et al . (2022), Bastos et al . (2023) 44 Oudemansiella canarii Physalacriaceae Edible Bastos et al . (2023) 46 Lentinus squarrosulus Polyporaceae Edible Li et al . (2021), Ishaq et al . (2022), Bastos et al . (2023) 47 Agaricus sp. Agaricaceae Edible Li et al . (2021) 50 Amylosporus campbellii Bondarwiaceae Edible Kabacia and Muchane, (2023) Declarations Ethics approval and consent to participate 'Not applicable' Consent for publication 'Not applicable' Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on request. Competing interests The authors declare that they have no competing interests Funding The research was partly funded by the UNESCO International Center for Biotechnology, University of Nigeria, Nsukka. Authors' contributions Conceptualization: CVO, NEA; Methodology and Investigation: CVO, NEA, CNO, EOO, OTO; Sampling: CVO, OVJ, MCA, KCU; Writing – Original Draft: CVO, MEM, UOE, AA; Writing – Review and Editing: MEM, CVO, AA; Visualization: CVO and MEM; Supervision: NEA; Data Curation: CVO, EOO, MEM. All authors read and approved the final manuscript. 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Nigeria.","correspondingAuthor":false,"prefix":"","firstName":"Eugene","middleName":"Obashi","lastName":"Ojua","suffix":""},{"id":636447157,"identity":"c9bd2e19-5499-4a3f-a516-db2e1c3f51f8","order_by":10,"name":"Musibau Emmanuel Momoh","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0006-0857-5070","institution":"2.\tDepartment of Plant Science and Biotechnology, University of Nigeria, Nsukka, Enugu State, Nigeria.","correspondingAuthor":true,"prefix":"","firstName":"Musibau","middleName":"Emmanuel","lastName":"Momoh","suffix":""}],"badges":[],"createdAt":"2026-05-07 20:48:44","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9646588/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9646588/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108978493,"identity":"2fd98e72-c9fd-41ff-8e4e-f9dfadcd8904","added_by":"auto","created_at":"2026-05-11 11:40:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":316382,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Southeast showing the five states (Ibe \u003cem\u003eet al\u003c/em\u003e., 2022).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9646588/v1/2c91d27959cb44e90c2255bc.png"},{"id":108978452,"identity":"faedfb9f-1a6f-4538-9d24-c2f10d200ee5","added_by":"auto","created_at":"2026-05-11 11:37:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":526734,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRooted Neighbour-Joining phylogram depicting the evolutionary relationships (phylogeny) among ITS gene sequences of sampled mushroom species. The names in parenthesis preceded by the accession numbers denote the closest Genbank relatives.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9646588/v1/68f3b9c826683d3b22807e77.png"},{"id":108978492,"identity":"bf0a7bad-0770-4035-91fb-297bab99db8b","added_by":"auto","created_at":"2026-05-11 11:38:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":315014,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRooted Neighbour-Joining phylogram depicting the evolutionary relationships (phylogeny) among ITS gene sequences of sampled mushroom species alongside closely related Genbank relatives. \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAspergillus niger\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e served as the outgroup.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9646588/v1/0aac3f046bf971c1b3e00ced.png"},{"id":108980452,"identity":"f8b8ca5a-cbce-45d1-b909-44ea97cce1fc","added_by":"auto","created_at":"2026-05-11 12:06:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1946461,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9646588/v1/b4a9fca2-a7bb-4db6-81bb-4d253582a5aa.pdf"},{"id":108978451,"identity":"97f6dcbb-aa2b-402b-ab75-89751a07a57d","added_by":"auto","created_at":"2026-05-11 11:37:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":9677616,"visible":true,"origin":"","legend":"","description":"","filename":"Plates.docx","url":"https://assets-eu.researchsquare.com/files/rs-9646588/v1/0906d426106b35a466d063de.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eMolecular Studies on the Diversity of Wild Mushrooms Indigenous to Southeastern Nigeria Using the Internal Transcribed Spacer (ITS) Region\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003e\u003cspan\u003eIn most part of Africa including Nigeria, mushrooms have become part of the diets of the common man due to their therapeutic and nutritional roles (Teke \u003cem\u003eet al\u003c/em\u003e., 2021). From time immemorial, most of the collections, characterization and documentations of mushroom species all over the world were based on the phenotypic traits of the fruiting bodies and preparation of cultures to distinguish between the mycelia of different mushroom species. Also, vernacular naming system and cultural traditions have been instrumental in discerning between mushroom species in some parts of the world (Tibuhwa, 2012). Although, these approaches are regularly used, they are tedious, consume time and may lack precision in differentiating interrelated species (Appiah \u003cem\u003eet al\u003c/em\u003e., 2017). Recently, use of biotechnological tools and molecular markers such as microsatellites, DNA barcodes and hosts of others have been introduced and adopted as the most efficient tools for species identification (Ao \u003cem\u003eet al\u003c/em\u003e., 2019).\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cspan\u003eDNA barcoding is a reputable biotechnological tool employed by most biologists in identifying and discriminating between living organisms up to the species level (Gosavi, 2016). They are highly sophisticated and overcomes most of the challenges of the traditional methods of identification (Xu, 2016). DNA barcoding utilizes short and standardized genetic sequence of 500 to 800 bp of the target sequences to classify species of all eukaryotic taxa using the most suitable primer for each taxonomic group (Ao \u003cem\u003eet al\u003c/em\u003e., 2019). The use of genetic barcodes for species identification was first introduced in 2003 by Paul Hebert and colleagues who used the Cytochrome oxidase 1 (CO1) region to differentiate between butterflies (Hebert \u003cem\u003eet al\u003c/em\u003e., 2003). Since then, DNA barcode have been effectively utilized to classify other animal species (Young \u003cem\u003eet al\u003c/em\u003e., 2019), protists (Pawlowski and Lecroq, 2010), fungi (Schoch \u003cem\u003eet al\u003c/em\u003e., 2012; Lucking \u003cem\u003eet al\u003c/em\u003e., 2020) and plants (Li \u003cem\u003eet al\u003c/em\u003e., 2011). Apart from species identification and diversity studies, DNA barcodes have been used to checkmate fraudulently labelled foods such as fishes, meats, mushrooms as well as herbal supplements (Simmler \u003cem\u003eet al\u003c/em\u003e., 2015; Zhao \u003cem\u003eet al\u003c/em\u003e., 2021).\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cspan\u003eFungi are ranked the second most specious organism belonging to the kingdom eukaryote, but study of their diversity has suffered limitations until recently due to lack of universally accepted DNA barcode marker (Khaund and Joshi, 2014). Finding an effective and broadly suitable barcode or molecular markers for fungal species identifications was tedious but recently a multinational collaborative consortium of mycologists endorsed the Internal Transcribed Spacer (ITS) area as the most suitable barcode marker for fungi identification and classification (Schoch \u003cem\u003eet al\u003c/em\u003e., 2012). The choice of ITS over other notable nuclear barcode markers such as small subunits (nSSU), large subunits (nLSU) and other protein-coding genes such as the largest subunit of RNA polymerase II (RPBI), second largest subunit of RNA polymerase II (RPB2) and minichromosome maintenance protein (MCM7) was probably due to its wide acceptability and efficiency in diversity studies of over seventeen (17) fungal families which include the Basidiomycota and Ascomycota that are the largest phyla in the fungal kingdom (Xu, 2016; Raja \u003cem\u003eet al\u003c/em\u003e., 2017).\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cspan\u003eSoutheast Nigeria is one of the major regions of Nigeria endowed with natural and wild growing mushrooms that are capable of bridging the nutritional gaps of the staple crops. Unfortunately, inconsistencies in morphological identifications and phobia of consuming poisonous mushroom species have resulted to gross negligence of mushrooms in the region. Lately, the use of biotechnological tools in species identifications has proven to be more precise and reliable. The use of DNA barcodes in fungal identifications have been reported by some authors in so many countries (Geiser \u003cem\u003eet al\u003c/em\u003e. 2007; Seena, \u003cem\u003eet al\u003c/em\u003e., 2010; Robideau \u003cem\u003eet al\u003c/em\u003e., 2011; Khaund and Joshi, 2014; Khodadadi \u003cem\u003eet al\u003c/em\u003e., 2014; Elwess \u003cem\u003eet al\u003c/em\u003e., 2016; Irinyi \u003cem\u003eet al\u003c/em\u003e., 2016). In Nigeria, the use of biotechnological tools such as barcode markers for mushroom diversity studies have not been properly harnessed. Very few diversity studies of mushrooms using DNA barcode in Nigeria have been reported; Adedokun \u003cem\u003eet al\u003c/em\u003e. (2016) who characterized the mushrooms of Niger Delta region of Nigeria and Adeniyi \u003cem\u003eet al\u003c/em\u003e. (2018) and Adebayo \u003cem\u003eet al\u003c/em\u003e. (2021) that worked in the western region of Nigeria, hence the need to investigate mushroom diversity in other regions of Nigeria such as Southeast which rely greatly on mushrooms as alternative for other expensive source of proteins and dietary nutrients.\u0026nbsp;\u003c/span\u003e\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy location\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSoutheast is one of the six (6) geopolitical zones of Nigeria which comprises five (5) states (Abia, Anambra, Ebonyi, Enugu and Imo) (Figure 1) out of the thirty six (36) states including Abuja, the federal capital territory (Anejionu \u003cem\u003eet al\u003c/em\u003e., 2013). The region is located within longitudes 6\u003csup\u003e0\u003c/sup\u003eE to 8\u003csup\u003e0\u003c/sup\u003eE and latitudes 5\u003csup\u003e0\u003c/sup\u003eN and 6\u003csup\u003e0\u003c/sup\u003eN (Osugiri \u003cem\u003eet al\u003c/em\u003e., 2019), with an estimated population of 16,395,554 and a land mass of 10,952,400 hectares (Ibe \u003cem\u003eet al\u003c/em\u003e., 2022). Southeast Nigeria predominantly belongs to the tropical rainforest zone, although the vegetation stretches from the derived savannah in the interior to the mangrove swamp in the coast (Okoroafor \u003cem\u003eet al\u003c/em\u003e., 2017). Distinguishing between the rainy and dry seasons are challenging, although rainy and dry seasons are more pronounced between May to October and November to April respectively. The region has an annual mean temperature of 28\u003csup\u003e0\u003c/sup\u003eC and annual rainfall of 2000 to 3000 mm (Osugiri \u003cem\u003eet al\u003c/em\u003e., 2019). People of southeast Nigeria are mostly the Igbo speaking tribe with unique culture and practice subsistence level of Agriculture under rain-fed conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample collection and preservation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFifty (50) mushrooms samples were collected randomly from various locations in the five (5) states of Southeastern Nigeria using the opportunistic method of sampling macrofungi or mushroom diversity (Lodge \u003cem\u003eet al\u003c/em\u003e., 2004; Prayudi \u003cem\u003eet al\u003c/em\u003e., 2019). Photographs of each mushroom sample were taken in situ before harvesting. They were harvested and put into separate paper bags and labelled properly. All the collected mushroom samples were transported to the department of Plant Science and Biotechnology and were oven-dried for 2 days at 50\u003csup\u003e0\u003c/sup\u003eC before taken to the Biotechnology Laboratory of the department of Biological Sciences, Godfrey Okoye University, Enugu for DNA extraction, gel electrophoresis, polymerase chain reaction. List of sampled mushrooms, date of collection, locality, state and their habitats are presented in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Lists of samples and their habitats, date of collection, town, local government and state of collection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"858\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSamples\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDate of collection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLGA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eState\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubstrate/Habitat\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e23/5/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eImilike-Agu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eUdenu\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e23/5/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eBotanic Garden UNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eNsukka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Tree Stump\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e25/5/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eIsuochi\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eUmunneochi\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAbia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e25/5/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eIsuochi\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eUmunneochi\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAbia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e25/5/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eIheakpu-Awka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIgbo-Eze South\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e25/5/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eUhunowerre\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIgbo-Eze South\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Tree Stump\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e30/5/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eArondiokoroji\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eOkigwe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eImo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Tree Stump\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e30/5/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eArondiokoroji\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eOkigwe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eImo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e30/5/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eIsuochi\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eUmunneochi\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAbia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e30/5/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eArondiokoroji\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eOkigwe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eImo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e1/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eUvuru\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eUzo-Uwani\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e1/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAmube\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIgbo-Eze North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Palm Tree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e3/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eOkoji Ula-Ekwulobia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAguata\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e3/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eOkoji Ula-Ekwulobia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAguata\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e3/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eNkwelle \u0026ndash;Ezunaka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eOyi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e3/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eNkwelle \u0026ndash;Ezunaka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eOyi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e3/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eNkwelle \u0026ndash;Ezunaka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eOyi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e5/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eUnadu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIgbo-Eze South\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e5/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eIwollo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eEzeagu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e6/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eOboro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIkwuano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAbia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e6/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eOboro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIkwuano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAbia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e6/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eOkoji Ula-Ekwulobia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAguata\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e8/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eUmuduru\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIsiala Mbano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eImo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e8/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eIbagwa-Aka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIgbo-Eze South\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Tree Stump\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e9/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eUturu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIsuikwuato\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAbia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e9/6/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eUturu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIsuikwuato\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAbia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e4/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAguleri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAnambra North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e5/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eUmuduru\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIsiala Mbano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eImo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e5/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eUmuduru\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIsiala Mbano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eImo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e5/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAwba-Ofemili\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAwka North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDecaying Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e12/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eUturu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIsuikwuato\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAbia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Tree Branch\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e12/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eObollo-Afor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eUdenu\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e12/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAguleri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAnambra North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Tree Stump\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e12/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAguleri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAnambra North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Palm Log\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e18/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAmufie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIgbo-Eze North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eTree Stump\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e18/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eUmuduru\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIsiala Mbano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eImo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e23/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003ePG Hostel UNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eNsukka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e23/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eOkata\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIgbo-Eze North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e23/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eObukpa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eNsukka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Mango Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e28/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eOboro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIkwuano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAbia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e29/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAwba-Ofemili\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAwka North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Palm Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e29/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eNdufu-Aliki Ikwo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIkwo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEbonyi\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Tree Trunk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e29/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAkokwa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIdeato North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eImo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e29/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAkokwa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIdeato North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eImo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e29/7/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003ePG Hostel UNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eNsukka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e7/8/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAguleri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAnambra North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e7/8/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAwba-Ofemili\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAwka-North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e7/8/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eIheakpu-Awka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIgbo-Eze South\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e7/8/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eIheakpu-Awka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eIgbo-Eze South\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.28471%;\"\u003e\n \u003cp\u003eS50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4026%;\"\u003e\n \u003cp\u003e7/8/2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.0373%;\"\u003e\n \u003cp\u003eAwba-Ofemili\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6698%;\"\u003e\n \u003cp\u003eAwka-North\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.1027%;\"\u003e\n \u003cp\u003eAnambra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5029%;\"\u003e\n \u003cp\u003eDead Wood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eDNA extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing the methodology of Adedokun \u003cem\u003eet al\u003c/em\u003e. (2016) the oven dried mushroom fruiting bodies were crushed into powder with the help of liquid nitrogen. Genomic DNA extraction was done using Zymo Research Quick-DNA Plant/Seed Miniprep kit (cat. D6020) following the manufacturers procedures. The quality of the extracted DNA was determined using 1% agarose gel electrophoresis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePCR amplification and sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe methodology and procedures of Cold Spring Harbor Laboratory (2014) was adopted. The internal transcribed spacer (ITS) regions ( ̴ 600 bp) of rRNA gene were amplified with ITS-5 forward (5\u0026acute;- GGA AGT AAA AGT CGT AAC AAG G - 3\u0026acute;) and ITS-4 reverse (5\u0026acute;- TCC TCC GCT TAT TGA TAT GC - 3\u0026acute;) primers according to White \u003cem\u003eet al\u003c/em\u003e. (1990) and Adedokun \u003cem\u003eet al\u003c/em\u003e. (2016). The primers were synthesized in a DNA synthesizer (Applied Biosystems, UK) at Inqaba Biotec Company, Pretoria (South Africa). PCR was carried out in a total volume of 25\u0026micro;l containing 2.0 \u0026micro;l of genomic DNA, 12.5 \u0026micro;l of 1 x PCR master mix (New England Biolabs, New York, NY, USA), 1.0 \u0026micro;l each of forward and reverse primer (10 mM) and 8.5 \u0026micro;l of H\u003csub\u003e2\u003c/sub\u003eO. The PCR products were viewed using 1% Agarose gel and Sybr green dye. The PCR was run at 100 v for 30 minutes. Amplifications were done in a thermal cycler with an initial denaturation step of 94\u003csup\u003eo\u003c/sup\u003eC for 3 minutes and followed by another 30 cycles of denaturation step at 90\u003csup\u003eo\u003c/sup\u003eC, annealing at 56\u003csup\u003eo\u003c/sup\u003eC and elongation for 72\u003csup\u003eo\u003c/sup\u003eC at 1 minute each. The final extension was done at 72\u003csup\u003eo\u003c/sup\u003eC for 10 minutes. The PCR products were sequenced at Inqaba Biotec Company, Pretoria, South Africa to obtain the nucleotide sequence of the DNA barcodes of the different mushroom samples. Three (3 \u0026mu;l) of the samples were diluted with 1 \u0026mu;l of primer and 3 \u0026mu;l milliq water before sequencing. Sequence analysis software v 6.2 from Thermos Fisher Inc were used to analyze the sequence (Adebayo \u003cem\u003eet al\u003c/em\u003e., 2021).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhylogenetic analysis of ITS region\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sequences were edited by trimming and assembling to obtain a consensus sequence data\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eusing the CLC work bench 6.9.1. (Adedokun \u003cem\u003eet al\u003c/em\u003e., 2016). Each of the nucleotide sequence was compared with the nucleotide sequence in the National Center for Biotechnology Information (NCBI), DNA Subway, Barcode of Life Database (BOLD) and UNITE databases using the Basic Local Alignment Search Tool (BLAST) to check for highest percentage identity score or the Lowest Expectation of E-value. The evolutionary history among different mushroom species was inferred using the Neighbor Joining method (Saitou and Nei, 1987). The bootstrap consensus tree inferred from 1000 replicates (Felsenstein, 1985\u003cstrong\u003e)\u003c/strong\u003e is taken to represent the evolutionary history of the taxa analyzed. Branches corresponding to partitions reproduced in less than 50% bootstrap replicates are collapsed. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) are shown next to the branches. The evolutionary distances were computed using the p-distance method (Nei and Kumar, 2000) and are in the units of the number of base differences per site. The analysis involved 42 nucleotide sequences. All positions containing gaps and missing data were eliminated (complete deletion option). There was a total of 162 positions in the final dataset. Evolutionary analyses were conducted in MEGA X (Kumar \u003cem\u003eet al\u003c/em\u003e., 2018). \u003cem\u003eAspergillus niger\u003c/em\u003e served as the outgroup. The purpose of including an outgroup is to establish the ancestral (basal) position in relation to the other taxa being analyzed. The outgroup provides insight into the evolutionary relationships among the taxa of interest. It serves as a reference point for determining ancestral and derived traits and rooting the tree to show the direction of evolutionary change.\u003c/p\u003e"},{"header":"RESULTS AND DISCUSSIONS","content":"\u003cp\u003eA total of 50 mushroom samples were collected from the 5 southeastern states of Nigeria (Table 1). Nine (9) mushroom samples were collected from 3 different local government areas in Abia State, while fourteen (14) samples were collected from 4 local government areas in Anambra State. In Ebonyi state, sample was collected from only one local government area. However, in Enugu state, 17 mushroom samples were collected from 6 different local government areas, while, 9 mushroom samples were collected from 3 different local government areas in Imo state. There were two (2) groups of mushroom samples based on the substrates they grew on. Twenty-nine (29) out of the 50 samples were found to grow on dead decaying woods, while the remaining 21 samples grow on the soil. Distribution of mushroom species as shown in this research is an indication of the prolific growth and development of wild mushrooms in Southeast Nigeria. Effective sampling of mushroom species between late May and early August was possible due to the boom in mushroom growth and development within the period. However, this boom may be connected to heavy rainfall and high humidity usually encountered in this zone during this period, since mushrooms with suitable substrates are known to flourish in areas with high humidity and rainfall. Previous researchers have demonstrated that mushrooms thrive exceptionally well in regions with high rainfall and humidity (Markson \u003cem\u003eet al\u003c/em\u003e., 2017; Adeniyi \u003cem\u003eet al\u003c/em\u003e., 2018; Titilawo \u003cem\u003eet al\u003c/em\u003e., 2022). Greater number of the sampled mushrooms were observed to grow on decaying logs of wood, while the remaining samples grew on soil and dead organic matter. The preference of dead decaying woods as substrates may be due to high lignocellulosic compounds in woods which are known to support macrofungi growth and development. Earlier researchers have shown that mushroom species flourish on a variety of substrates but prefer lignin, cellulose and organic matter rich substrates (Titilawo \u003cem\u003eet al\u003c/em\u003e., 2022).\u003c/p\u003e\n\u003cp\u003eAgarose gel electrophoresis 1 % (w/v) analysis on the presence and quality of extracted genomic DNA showed and confirmed the presence of genomic DNA molecules from the mushroom samples, although with band quality ranging from sharp to very faint. Variations in the quality of DNA extracted from the sampled mushrooms as revealed by the bands in the agarose gel pictures is an indication that, DNA were successfully extracted, but their quality may have been influenced by factors such as adopted protocol, technicalities and type of organism. Earlier report has shown that varied organism, genotype and even cultivars may respond differently to DNA extraction protocols (Ganiyu \u003cem\u003eet al\u003c/em\u003e., 2017). The PCR products of the ITS gene (900 \u0026ndash; 1000 bp) loaded in agarose gel 1 % (w/v) and viewed using high-performance UV transilluminator showed conspicuous bands in all the amplified samples except in only few cases that showed faint bands. Bands of the PCR products as was revealed by the agarose gel pictures is a clear-cut sign that the ITS region (900 \u0026ndash; 1000 bp) was successfully amplified. However, the quality of the bands varied across the samples and this may be ascribed to the differences in genetic backgrounds and the resulting wide variations in bioactive compositions of the sampled mushrooms. Studies before now have demonstrated that, abundance of bioactive compounds such as polyphenols, polysaccharides and tannin influence the oxidation and degradation of DNA, resulting in the failure of PCR (Arruda \u003cem\u003eet al\u003c/em\u003e., 2017).\u003c/p\u003e\n\u003cp\u003eThe BLAST results from DNA subway, NCBI, BOLD and UNITE as depicted in Table 2 \u0026nbsp; \u0026nbsp;identified most of the mushroom samples. \u0026nbsp;Over a quarter of the sampled mushrooms (S4, S7, S12, S15, S18, S25, S32, S36, S38, S39, S43, S44, S46 and S47) had similar identifications up to the species level using the four databases. Moreover, some of the mushroom samples were identified by the four databases to belong to the same genus but varied in their species identifications. For instance, while the DNA subway, NCBI and UNITE databases identified sample 1 as \u003cem\u003eAmanita nauseosa\u003c/em\u003e, the BOLD identified the sample as \u003cem\u003eAmanita manicata\u003c/em\u003e. Similar trend was observed in samples 2, 6, 8, 9, 14, 17, 22, 24, 27, 28, 30, 31, 33, 35, 37 and 42 (Table 2). In other samples, the four databases lacked consistency in identifying the genus of the samples. For example, sample 5 was identified as \u003cem\u003eMarasmiellus sp.\u003c/em\u003e by the DNA subway, NCBI and BOLD databases, while the UNITE database identified it as \u003cem\u003eCampanella junghuhnii\u003c/em\u003e. This was also observed in samples 10, 20, 23, 26, 31, 35, 40, 41 and 50 (Table 2). However, sample 14 could not be identified using the DNA subway. Sample 16 was identified as an uncultured fungus by both the DNA subway and the NCBI, while the BOLD and UNITE identified it as \u003cem\u003eGanoderma lucidum.\u0026nbsp;\u003c/em\u003eThe efficiency of NCBI database in identifying most of the mushroom samples up to the species level could be linked to its wide applications and coverage. While the NCBI serves as a general database for all organism irrespective of sequence region, the DNA subway is a subset of the NCBI with limited data. The BOLD and UNITE databases focus more on the fungi and ITS region respectively, which may possibly limit their utility in fungi identifications (Raja \u003cem\u003eet al\u003c/em\u003e., 2017). Nevertheless, molecular identification of organisms in more than one database could be helpful in authenticating the identity of an organism. This observation explains the reason why NCBI database have been used in molecular identifications of virtually all organisms.\u003c/p\u003e\n\u003cp\u003ePrecise identifications of mushrooms will clarify the uncertainties surrounding their usage in drug development and formulation of nutritional supplements. According to Adeniyi \u003cem\u003eet al\u003c/em\u003e. (2018), correct taxonomical identification of any organism is fundamental and germane to their use in further studies. Successful identification of the sampled mushrooms using their ITS region confirms its efficacy in molecular characterization of mushrooms. This agrees with Schoch \u003cem\u003eet al\u003c/em\u003e. (2012), which confirmed the ITS region as the most potent and effective barcode marker for molecular identifications of fungi. Although, the BLAST results showed some consistency in identification of some mushroom samples across different databases, others were not consistent. However, the discrepancies may be connected to the inconsistencies in submission of sequences in databases, since close to 27% of fungal ITS sequences submitted in the databases are insufficiently identified taxonomically (Nilsson \u003cem\u003eet al\u003c/em\u003e., 2006; Raja \u003cem\u003eet al\u003c/em\u003e., 2017). More so, it is estimated that approximately 20% of the fungal sequences in the databases may be incorrectly annotated, although they may differ greatly based on taxonomic groups (Raja \u003cem\u003eet al\u003c/em\u003e., 2017). Similarity percentage of most of our sampled mushroom sequences and its Genbank relatives are less than 100% and Oyetayo (2014) suggested that this situation could be linked to variations in ecological zones. The query length of the identified mushroom species ranged from 395 \u0026ndash; 770 as found in sample 18 and 50 respectively. However, the percentage identity score of the mushroom samples ranged from 71.23 \u0026ndash; 100. \u0026nbsp;More so, it is worthy to note that all the identified mushroom species had an E-value of 0.00 except for the cases of sample 16, 18, 21 and 23 that had higher E-values (Table 2). The accession numbers and all the associated information of all the identified mushrooms are presented in Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe families of the sampled mushrooms as represented in Table 3 divided all the 41 identified mushrooms into 11 families; polyporaceae (13) representing 31.707% of the identified mushrooms and Agaricaceae (9) which represented 21.951% of the identified mushrooms. Family Omphatotaceae had 7 mushrooms samples and represented 17.073% of the identified mushroom samples. Family Ganodermataceae and Marasmiaceae had 4 and 2 samples, respectively which represented 9.756% and 4. 878% of the entire identified mushrooms. Other, families such as Amanitaceae, Auriculariaceae, Russulaceae, Hypoxylaceae, Physalacriaceae and Bondarwiaceae had 1 mushroom each which represented 2.439% each of the entire identified mushrooms. Greater number of mushrooms samples belonging to the family Polyporaceae recorded in this study signifies their abundance in the region. Their abundance in the region may be associated with their versatility in the choice of substrates and ability to thrive in the prevailing environmental conditions. Similar trend was reported in the wild mushrooms of Niger Delta of Nigeria, where family Polyporaceae had the highest number of samples (40.4%) of all the sampled mushrooms (Adedokun \u003cem\u003eet al\u003c/em\u003e., 2016). More so, Apollos \u003cem\u003eet al\u003c/em\u003e. (2017) worked on the molecular characterization of mushrooms in Kogi State and reported that Polyporaceae accounted for majority of the sampled mushrooms (60%). Elsewhere, Appiah \u003cem\u003eet al\u003c/em\u003e. (2017) reported that Polyporaceae was the most abundant (33.33%) in some Ghana mushrooms. Molecular characterization of 56 mushrooms sampled at Adirondack Park had family Russulaceae (12.5%) as the most abundant and family Polyporaceae (8.93%) as the second most abundant (Elwess \u003cem\u003eet al\u003c/em\u003e., 2016). In sharp contrast to the findings of this study, Adeniyi \u003cem\u003eet al\u003c/em\u003e. (2018) reported family Tricholomataceae (52.63%) as the most abundant while Polyporaceae family was not recorded in some wild mushrooms of Nigeria. The differences may be attributed to the sampling methods adopted or the time of sampling, since they share to some extent similar environmental conditions. Identifications of Mushroom species belonging to families such as Agaricaceae and Omphatotaceae that ranked second and third, respectively indicate that large numbers could be found in the region if the number of samples are increased. More so, mushroom families such as Ganodermataceae, Marasmiaceae, Amanitaceae, Auriculariaceae, Russulaceae, Hypoxylaceae, Physalacriaceae and Bondarwiaceae found in varying amounts confirms their presence and indicate that more representative species may be found in the region with a more intense sampling. A total of 11 different families recorded in this study differ from 19 families reported by\u0026nbsp;Elwess \u003cem\u003eet al\u003c/em\u003e. (2016), 13 families by Adedokun \u003cem\u003eet al\u003c/em\u003e. (2016), 5 families by Apollos \u003cem\u003eet al\u003c/em\u003e. (2017) and 4 families by Adeniyi \u003cem\u003eet al\u003c/em\u003e. (2018). However, since the number of samples studied by each author varied, it will be reasonable to suggest that variations in the number of families may have a direct link with the number of samples studied\u003c/p\u003e\n\u003cp\u003eThe 41 identified mushrooms were classified into 17 different genera with \u003cem\u003eTrametes\u003c/em\u003e (7) being the most abundant and followed by \u003cem\u003eLentinus\u0026nbsp;\u003c/em\u003e(6). They were followed by other genera such as \u003cem\u003eNeonothopanus\u003c/em\u003e (5), \u003cem\u003eGanoderma\u0026nbsp;\u003c/em\u003e(4), \u003cem\u003eLeucocoprinus\u0026nbsp;\u003c/em\u003e(3), \u003cem\u003eChlorophyllum\u0026nbsp;\u003c/em\u003e(3). Genera such as \u003cem\u003eAgaricus\u003c/em\u003e and \u003cem\u003eMarasmius\u003c/em\u003e had 2 samples each, while genera such as \u003cem\u003eAuricularia, Microsalliota, Daldinia, Oudemansiella, Amanita, Amylosporus, Lactifluus, Marasmiellus\u003c/em\u003e and \u003cem\u003eGumnopus\u003c/em\u003e had 1 sample each. More so, the sampled mushrooms were classified into 19 different species with 5 genera which could not be identified up to the species level. \u003cem\u003eTrametes\u003c/em\u003e was evidently the most abundant genus found in this study and was followed by \u003cem\u003eLentinus spp\u003c/em\u003e. Although \u003cem\u003eLentinus\u003c/em\u003e \u003cem\u003esquarrosulus\u003c/em\u003e was not the most abundant sampled genus, they were remarkably high and compared favourably with the report of Adedokun \u003cem\u003eet al\u003c/em\u003e. (2016) that reported them as the most abundant sampled mushrooms with 19 samples. The finding is evidence that \u003cem\u003eTrametes spp\u0026nbsp;\u003c/em\u003eand \u003cem\u003eLentinus\u003c/em\u003e \u003cem\u003esquarrosulus\u0026nbsp;\u003c/em\u003emay be highly distributed in Nigeria especially within the tropical and derived savannah vegetation zones.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe edibility status of the sampled mushrooms was computed using reliable reference articles (Table 3). In line with the articles, we were able to characterize our samples into edible, non-edible and unknown categories. Twenty-eight (28) samples which represent 68.293% of the 41 identified mushrooms are edible. Eleven (11) samples which represent 26.829% of the identified mushrooms are non-edible, while 2 samples (4.878%) have unknown edibility status. The edible status of majority of the sampled mushrooms indicates that the region is endowed with mushroom species that can be consumed for nutritional and medicinal purposes. Distinguishing between edible and non-edible mushrooms have been based on traditional knowledge, folk tales and in recent times chemical analysis. Unfortunately, these methods are not reliable and may expose one to poisoning if the wrong species are consumed. Nevertheless, efforts are now geared towards discerning between edible and non-edible species through molecular identifications. These molecular identifications could encourage mushroom foraging and enable the populace harness the full potentials of these mushrooms in diets and medicines. More so, important constituents which can be used in drug and supplement formulations can be extracted from non-edible species.\u003c/p\u003e\n\u003cp\u003ePhylogram showing the evolutionary relatedness of the sampled mushrooms disclosed they clustered distinctly (Figure 2). Sample 14 ITS which was closely identified as \u003cem\u003eTrametes polyzona\u0026nbsp;\u003c/em\u003eis a basal taxon and it indicates that the taxa/species has the ability to remain relatively unchanged and has maintained most ancestral traits overtime or may have not undergone significant evolutionary modifications. Although, 14 ITS was closely identified as samples 28 ITS, 33 ITS and, 26 ITS to the species level (\u003cem\u003eTrametes polyzona\u003c/em\u003e) and identified to belong to the same genera as 31 ITS, 35 ITS and 40 ITS (\u003cem\u003eTrametes parvispora\u003c/em\u003e), they were not classified in the same clade due to evolutionary distance. The distinct clustering suggests that the species have relatively large genetic or evolutionary distances between them. While samples 28 ITS, 33 ITS and, 26 ITS each had about 99.8% identity with \u003cem\u003eTrametes polyzona,\u0026nbsp;\u003c/em\u003esample 14 ITS had just 85% identity to its closest Genbank relative, \u003cem\u003eTrametes polyzona.\u003c/em\u003e However, samples 28 ITS, 33 ITS and, 26 ITS do not belong to the same species, but are more related to 31 ITS, 35 ITS and 40 ITS than they are to 14 ITS.\u003c/p\u003e\n\u003cp\u003eGroup of mushroom species, (28 ITS, 33 ITS, 26 ITS) which formed a polytomy including the subsequent listed groups of mushroom species (31 ITS, 35 ITS, 40 ITS), (41 ITS, 25 ITS, 20 ITS), (17 ITS, 27 ITS, 37 ITS), (12 ITS, 4 ITS, 25 ITS), (8 ITS, 22 ITS, 30 ITS), clearly revealed multifurcation which could be as a result of insufficient genetic or morphological data to determine the exact evolutionary changes. The multifurcation could also be due to complexity of evolutionary history or uncertainty about the relationships among the taxa. The species in each of the listed groups, (43 ITS and 46 ITS), (15 ITS and18 ITS), (28 ITS and 33B ITS), (35 ITS and 40 ITS), (21 ITS and 24 ITS), (16A ITS and 21A ITS), (4 ITS and 25 ITS), (32 ITS and 47 ITS), (27 ITS and 37 ITS), (39 ITS and 44 ITS), (5 ITS and 41 ITS), (6 ITS and 42 ITS) are sister taxa, which signifies that they share a more recent common ancestor with each other than with any other taxa in the tree. These groups of taxa, (43 ITS and 46 ITS), (15 ITS and18 ITS), (28 ITS and 33 ITS), (35 ITS and 40 ITS), (21 ITS and 24 ITS), (16 ITS and 21 ITS), (4 ITS and 25 ITS), (32 ITS and 47 ITS), (27 ITS and 37 ITS), (39 ITS and 44 ITS), (5 ITS and 41 ITS), (6 ITS and 42 ITS) together with their common ancestor (node) formed a monophyletic group which show they have a common ancestral population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDistinct clustering of the sampled mushroom species in this study and its Genbank relatives indicates the novelty of the collected mushroom species as none of the samples except 14 ITS formed a clade with their closest Genbank relatives (Figure 3). The distinct separation clearly indicates the need for further studies on the sampled mushroom species. Similar finding was made by Adeniyi \u003cem\u003eet al\u003c/em\u003e. (2018), where they observed distinct clustering of the sampled mushroom with the reference Genbank relatives and suggested disparity in nucleotide signature may be responsible. Aremu and Babalola (2015) also stated that differences in nucleotide compositions could amount to distinct clustering of species with its Genbank relatives.\u0026nbsp;\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eNotwithstanding the widespread developments, urbanization and climate change that has grossly affected biodiversity, wild mushrooms were still found in substantial amounts in Southeast Nigeria. However, the isolated mushrooms varied widely within families, genera and even species. Successful extraction of DNA from the sampled mushrooms using Zymo Research Quick-DNA Plant/Seed Miniprep kit confirm its extraction potency, while the amplification successes of the ITS region using the PCR indicate high amplification rate of the region. Sequencing rate of 82% recorded could be ascribed to quality of the amplified DNA and not due to sequencing failures. The BLAST reports shows that the ITS region was very effective in identifying the sampled mushrooms up to the species level. Highest number of mushrooms samples belonging to Polyporaceae family suggest they are the most distributed mushroom family in the region. Out of the identified mushroom samples, \u003cem\u003eTrametes spp\u003c/em\u003e and \u003cem\u003eLentinus squarrosulus\u0026nbsp;\u003c/em\u003ewere very abundant in the region, while other species such as \u003cem\u003eGanoderma spp\u003c/em\u003e, \u003cem\u003eNeonothopanus spp\u003c/em\u003e, \u003cem\u003eChlorophyllum spp\u003c/em\u003e and so on were also found in good quantities. Nonetheless, with more intense sampling, a greater number of mushroom species belonging to different families may be encountered. The evolutionary relationship of the sampled mushrooms as depicted by the phylogram showed they had distinctive ancestral lineages. Apart from 14 ITS that clustered differently with its closest relatives, other closely related species clustered and formed unique clades that shared similar ancestral lineages. The distinctive clustering of the sampled mushrooms and their Genbank relatives indicates the novelty of the sampled mushrooms and the need for more studies on the diversity of mushrooms in southeast Nigeria using molecular identifications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Depicts the Sequence source organism (top hit), Percentage Identity, Query Coverage, Total Score and Accession number\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"960\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6.25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS/N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.875%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuery Length\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequenced Source Organisms (Top Hit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDNA SUBWAY\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.75%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequenced Source Organisms (Top Hit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNCBI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBOLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUNITE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.375%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIdentity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.5%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuery Cover\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eE-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.625%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccession Number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6.25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.875%;\"\u003e\n \u003cp\u003e672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15%;\"\u003e\n \u003cp\u003e\u003cem\u003eAmanita nauseosa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.75%;\"\u003e\n \u003cp\u003e\u003cem\u003eAmanita nauseosa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eAmanita manicata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eAmanita nauseosa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.375%;\"\u003e\n \u003cp\u003e99.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.5%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.625%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.625%;\"\u003e\n \u003cp\u003eHQ625013.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6.25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.875%;\"\u003e\n \u003cp\u003e572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma mbrekobenum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.75%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma mbrekobenum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma applanatum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma applanatum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.375%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.5%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.625%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.625%;\"\u003e\n \u003cp\u003eKX000898.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6.25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.875%;\"\u003e\n \u003cp\u003e677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cepistipes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.75%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cepistipes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cepistipes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cepistipes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.375%;\"\u003e\n \u003cp\u003e98.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.5%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.625%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.625%;\"\u003e\n \u003cp\u003eMK412593.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6.25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.875%;\"\u003e\n \u003cp\u003e584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmiellus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.75%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmiellus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmiellus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eCampanella junghuhnii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.375%;\"\u003e\n \u003cp\u003e95.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.5%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.625%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.625%;\"\u003e\n \u003cp\u003eMK167361.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6.25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.875%;\"\u003e\n \u003cp\u003e605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.75%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus sp\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus nambi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.375%;\"\u003e\n \u003cp\u003e98.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.5%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.625%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.625%;\"\u003e\n \u003cp\u003eMW298684.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6.25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.875%;\"\u003e\n \u003cp\u003e607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.75%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.375%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.5%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.625%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.625%;\"\u003e\n \u003cp\u003eKT120037.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6.25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.875%;\"\u003e\n \u003cp\u003e588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.75%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus nambi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.375%;\"\u003e\n \u003cp\u003e98.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.5%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.625%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.625%;\"\u003e\n \u003cp\u003eMK931357.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6.25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.875%;\"\u003e\n \u003cp\u003e542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15%;\"\u003e\n \u003cp\u003e\u003cem\u003eAuricularia polytricha\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.75%;\"\u003e\n \u003cp\u003e\u003cem\u003eAuricularia polytricha\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eAuriculariaauricula-judae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eAuricularia cornea\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.375%;\"\u003e\n \u003cp\u003e99.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.5%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.625%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.625%;\"\u003e\n \u003cp\u003eKT273351.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6.25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.875%;\"\u003e\n \u003cp\u003e671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmius corrugatiformis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.75%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmius corrugatiformis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003ePouzarella dysthales\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.5%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmius pellucidus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.375%;\"\u003e\n \u003cp\u003e93.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.5%;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.625%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.625%;\"\u003e\n \u003cp\u003eKX953757.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"936\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.33618%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS/N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.36393%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuery Length\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.9808%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequenced Source Organisms (Top Hit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDNA SUBWAY\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3404%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequenced Source Organisms (Top Hit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNCBI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBOLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUNITE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.81857%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIdentity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.47065%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuery Cover\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.97652%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eE-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3127%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccession Number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.33618%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.36393%;\"\u003e\n \u003cp\u003e629\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.9808%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cretaceous\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3404%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cretaceous\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cretaceous\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cretaceous\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.81857%;\"\u003e\n \u003cp\u003e99.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.47065%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.97652%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3127%;\"\u003e\n \u003cp\u003eMN483022.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.33618%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.36393%;\"\u003e\n \u003cp\u003e694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.9808%;\"\u003e\n \u003cp\u003e\u003cem\u003eNull\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3404%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes sanguinea\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.81857%;\"\u003e\n \u003cp\u003e85.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.47065%;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.97652%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3127%;\"\u003e\n \u003cp\u003eOL685335.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.33618%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.36393%;\"\u003e\n \u003cp\u003e414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.9808%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3404%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.81857%;\"\u003e\n \u003cp\u003e94.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.47065%;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.97652%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3127%;\"\u003e\n \u003cp\u003eKT120055.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.33618%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.36393%;\"\u003e\n \u003cp\u003e499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.9808%;\"\u003e\n \u003cp\u003e\u003cem\u003eUncultured fungus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3404%;\"\u003e\n \u003cp\u003e\u003cem\u003eUncultured fungus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma lucidum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma lucidum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.81857%;\"\u003e\n \u003cp\u003e85.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.47065%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.97652%;\"\u003e\n \u003cp\u003e2.79-83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3127%;\"\u003e\n \u003cp\u003eLR993654.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.33618%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.36393%;\"\u003e\n \u003cp\u003e686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.9808%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum palaeotropicum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3404%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum palaeotropicum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum molybdites\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum palaeotropicum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.81857%;\"\u003e\n \u003cp\u003e94.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.47065%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.97652%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3127%;\"\u003e\n \u003cp\u003eMN318425.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.33618%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.36393%;\"\u003e\n \u003cp\u003e395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.9808%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3404%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.81857%;\"\u003e\n \u003cp\u003e87.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.47065%;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.97652%;\"\u003e\n \u003cp\u003e3e-156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3127%;\"\u003e\n \u003cp\u003eKT120055.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.33618%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.36393%;\"\u003e\n \u003cp\u003ePS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.9808%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3404%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.81857%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.47065%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.97652%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3127%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.33618%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.36393%;\"\u003e\n \u003cp\u003e622\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.9808%;\"\u003e\n \u003cp\u003e\u003cem\u003eMicropsalliota sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3404%;\"\u003e\n \u003cp\u003e\u003cem\u003eMicropsalliota sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eMicropsalliota globocystis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003eLycoperdaceae sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.81857%;\"\u003e\n \u003cp\u003e90.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.47065%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.97652%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3127%;\"\u003e\n \u003cp\u003eOM397374.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.33618%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.36393%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.9808%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3404%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7001%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.81857%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.47065%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.97652%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.3127%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"918\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.22876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS/N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.18954%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuery Length\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequenced Source Organisms (Top Hit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDNA SUBWAY\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequenced Source Organisms (Top Hit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNCBI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5076%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBOLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6362%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUNITE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.80392%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIdentity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuery Cover\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eE-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccession Number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.22876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.18954%;\"\u003e\n \u003cp\u003e573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanodrma sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanodrma sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5076%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma lucidum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6362%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma lucidum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.80392%;\"\u003e\n \u003cp\u003e97.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e1.94E-93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eKT120034.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.22876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.18954%;\"\u003e\n \u003cp\u003e567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5076%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6362%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus nambi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.80392%;\"\u003e\n \u003cp\u003e98.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eMK931357.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.22876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.18954%;\"\u003e\n \u003cp\u003e611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eLactifluus bicapillus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eLactifluus bicapillus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5076%;\"\u003e\n \u003cp\u003e\u003cem\u003eLactarius\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003cem\u003erubroviolascens\u003c/em\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6362%;\"\u003e\n \u003cp\u003e\u003cem\u003eLactifluus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.80392%;\"\u003e\n \u003cp\u003e71.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e8e-127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eMH549203.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.22876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.18954%;\"\u003e\n \u003cp\u003e583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma mbrekobenum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma mbrekobenum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5076%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma applanatum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6362%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma applanatum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.80392%;\"\u003e\n \u003cp\u003e95.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eKX000898.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.22876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.18954%;\"\u003e\n \u003cp\u003e675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cepistipes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cepistipes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5076%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cepistipes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6362%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cepistipes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.80392%;\"\u003e\n \u003cp\u003e98.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eMK412593.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.22876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.18954%;\"\u003e\n \u003cp\u003e517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5076%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6362%;\"\u003e\n \u003cp\u003e\u003cem\u003eLenzites sp\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.80392%;\"\u003e\n \u003cp\u003e99.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eMH855813.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.22876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.18954%;\"\u003e\n \u003cp\u003e703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllus globosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllus globosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5076%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum globosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6362%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum molybdites\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.80392%;\"\u003e\n \u003cp\u003e99.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eMH287459.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.22876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.18954%;\"\u003e\n \u003cp\u003e564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5076%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6362%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes hirsute\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.80392%;\"\u003e\n \u003cp\u003e99.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eMH131681.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.22876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e29\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.18954%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.7255%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5076%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6362%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.80392%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.53595%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cem\u003ePS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"936\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.12821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS/N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuery Length\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.4615%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequenced Source Organisms (Top Hit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDNA SUBWAY\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequenced Source Organisms (Top Hit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNCBI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBOLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUNITE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.61538%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIdentity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.33333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuery Cover\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eE-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8974%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccession Number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.12821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.4615%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus nambi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.61538%;\"\u003e\n \u003cp\u003e98.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.33333%;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8974%;\"\u003e\n \u003cp\u003eMK931357.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.12821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e31\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.4615%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes parvispora\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes parvispora\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes meyenii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eLenzites warnieri\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.61538%;\"\u003e\n \u003cp\u003e99.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.33333%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8974%;\"\u003e\n \u003cp\u003eMK736990.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.12821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e32\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.4615%;\"\u003e\n \u003cp\u003e\u003cem\u003eAgaricus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eAgaricus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eAgaricus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eAgaricus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.61538%;\"\u003e\n \u003cp\u003e96.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.33333%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8974%;\"\u003e\n \u003cp\u003eKJ540956.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.12821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e33\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.4615%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes hirsute\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.61538%;\"\u003e\n \u003cp\u003e99.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.33333%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8974%;\"\u003e\n \u003cp\u003eMH131681.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.12821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e35\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.4615%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes parvispora\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes parvispora\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes meyenii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eLenzites warnieri\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.61538%;\"\u003e\n \u003cp\u003e99.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.33333%;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8974%;\"\u003e\n \u003cp\u003eMK736990.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.12821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.4615%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.61538%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.33333%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8974%;\"\u003e\n \u003cp\u003eKT273380.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.12821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.4615%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum globosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum globosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum globosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum molybdites\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.61538%;\"\u003e\n \u003cp\u003e99.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.33333%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8974%;\"\u003e\n \u003cp\u003eKJ524553.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.12821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.4615%;\"\u003e\n \u003cp\u003e\u003cem\u003eGymnopus aff. Brunneigracilis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eGymnopus aff. Brunneigracilis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eGymnopus brunneigracilis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eGymnopus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.61538%;\"\u003e\n \u003cp\u003e97.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.33333%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8974%;\"\u003e\n \u003cp\u003eMF100983.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.12821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.4615%;\"\u003e\n \u003cp\u003e\u003cem\u003eDaldinia eschscholtzii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eDaldinia eschscholtzii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eDaldinia eschscholtzii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8205%;\"\u003e\n \u003cp\u003e\u003cem\u003eDaldinia eschscholtzii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.61538%;\"\u003e\n \u003cp\u003e99.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.33333%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.05128%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8974%;\"\u003e\n \u003cp\u003eMT507855.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"975\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.64103%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS/N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuery Length\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.8462%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequenced Source Organisms (Top Hit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDNA SUBWAY\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequenced Source Organisms (Top Hit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNCBI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBOLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUNITE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.4359%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIdentity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.20513%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuery Cover\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eE-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.2821%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccession Number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.64103%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e40\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.8462%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes parvispora\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes parvispora\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes meyenii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eLenzites warnieri\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.4359%;\"\u003e\n \u003cp\u003e99.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.20513%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.2821%;\"\u003e\n \u003cp\u003eMK736990.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.64103%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e41\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.8462%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmius palmivorus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmius palmivorus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmius sp\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eCampanella junghuhnii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.4359%;\"\u003e\n \u003cp\u003e96.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.20513%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.2821%;\"\u003e\n \u003cp\u003eMH131681.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.64103%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e42\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.8462%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus nambi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.4359%;\"\u003e\n \u003cp\u003e99.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.20513%;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.2821%;\"\u003e\n \u003cp\u003eMK931357.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.64103%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e43\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.8462%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.4359%;\"\u003e\n \u003cp\u003e99.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.20513%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.2821%;\"\u003e\n \u003cp\u003eMH172168.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.64103%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.8462%;\"\u003e\n \u003cp\u003e\u003cem\u003eOudemansiella canarii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eOudemansiella canarii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eOudemansiella canarii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eOudemansiella sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.4359%;\"\u003e\n \u003cp\u003e98.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.20513%;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.2821%;\"\u003e\n \u003cp\u003eAY216473.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.64103%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e46\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.8462%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.4359%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.20513%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.2821%;\"\u003e\n \u003cp\u003eMH172168.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.64103%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e47\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.8462%;\"\u003e\n \u003cp\u003e\u003cem\u003eAgaricus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eAgaricus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eAgaricus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eAgaricus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.4359%;\"\u003e\n \u003cp\u003e96.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.20513%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.2821%;\"\u003e\n \u003cp\u003eKJ540956.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.64103%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.8462%;\"\u003e\n \u003cp\u003e\u003cem\u003eAmylosporus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eAmylosporus campbellii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eAmylosporus campbellii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6154%;\"\u003e\n \u003cp\u003e\u003cem\u003eScytinostromella nannfeldtii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.4359%;\"\u003e\n \u003cp\u003e97.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.20513%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87179%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.2821%;\"\u003e\n \u003cp\u003eON033917.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKEY: PS = Poor Sequence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Summarized table showing mushroom identification, family and edibility status\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"714\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample Number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIdentified Mushrooms\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEdibility Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eAmanita nauseosa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAmanitaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma mbrekobenum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eGanodermataceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eHapuarachchi\u0026nbsp;\u003cem\u003eet al\u003c/em\u003e. (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cepistipes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAgaricaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmiellus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eOmphatotaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eOmphatotaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021), Ishaq \u003cem\u003eet al\u003c/em\u003e. (2022), Bastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eOmphatotaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eAuricularia polytricha\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAuriculariaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmius corrugatiformis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eMarasmiaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021), Bastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cretaceous\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAgaricaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021), Ishaq \u003cem\u003eet al\u003c/em\u003e. (2022), Bastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma lucidum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eGanodermataceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eHapuarachchi\u0026nbsp;\u003cem\u003eet al\u003c/em\u003e. (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum palaeotropicum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAgaricaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021), Ishaq \u003cem\u003eet al\u003c/em\u003e. (2022), Bastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eMicropsalliota sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAgaricaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanodrma sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eGanodermataceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eHapuarachchi\u0026nbsp;\u003cem\u003eet al\u003c/em\u003e. (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eOmphatotaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eLactifluus bicapillus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eRussulaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eGanoderma mbrekobenum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eGanodermataceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eHapuarachchi\u0026nbsp;\u003cem\u003eet al\u003c/em\u003e. (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eLeucocoprinus cepistipes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAgaricaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllus globosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAgaricaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eOmphatotaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes parvispora\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eAgaricus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAgaricaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes polyzona\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes parvispora\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021), Ishaq \u003cem\u003eet al\u003c/em\u003e. (2022), Bastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorophyllum globosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAgaricaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eGymnopus aff. Brunneigracilis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eOmphalotaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eDaldinia eschscholtzii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eHypoxylaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eTrametes parvispora\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eNon-edible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eMarasmius palmivorus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eMarasmiaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021), Bastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eNeonothopanus hygrophanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eOmphatotaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021), Ishaq \u003cem\u003eet al\u003c/em\u003e. (2022), Bastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eOudemansiella canarii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePhysalacriaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eBastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eLentinus squarrosulus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003ePolyporaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021), Ishaq \u003cem\u003eet al\u003c/em\u003e. (2022), Bastos \u003cem\u003eet al\u003c/em\u003e. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eAgaricus sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eAgaricaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eLi \u003cem\u003eet al\u003c/em\u003e. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.084%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.0924%;\"\u003e\n \u003cp\u003e\u003cem\u003eAmylosporus campbellii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.4874%;\"\u003e\n \u003cp\u003eBondarwiaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEdible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.0504%;\"\u003e\n \u003cp\u003eKabacia and Muchane, (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026apos;Not applicable\u0026apos;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026apos;Not applicable\u0026apos;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was partly funded by the UNESCO International Center for Biotechnology, University of Nigeria, Nsukka.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: CVO, NEA; Methodology and Investigation: CVO, NEA, CNO, EOO, OTO; Sampling: CVO, OVJ, MCA, KCU; Writing \u0026ndash; Original Draft: CVO, MEM, UOE, AA; Writing \u0026ndash; Review and Editing: MEM, CVO, AA; Visualization: CVO and MEM; Supervision: NEA; Data Curation: CVO, EOO, MEM. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026apos;Not applicable\u0026apos;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026apos;Not applicable\u0026apos;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFootnotes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026apos;Not applicable\u0026apos;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdebayo EA, Elkanah FA, Afolabi FJ, Ogundun OS, Alabi TF, Oduoye OT. Molecular characterization of most cultivated Pleurotus species in sub-western region of Nigeria with development of cost-effective protocol on palm oil waste. Heliyon. 2021;7:e06215. \u003c/li\u003e\n\u003cli\u003eAdedokun OM, Kyalo M, Gnonlonfin B, Wainaina J, Githae D, Skilton R, et al. Mushrooms: molecular characterization of indigenous species in the Niger Delta region of Nigeria. Eur J Hortic Sci. 2016;81(5):273-80. \u003c/li\u003e\n\u003cli\u003eAdeniyi M, Titilawo Y, Oluduro A, Odeyemi O, Nakin M, Okoh AI. Molecular identification of some wild Nigerian mushrooms using internal transcribed spacer polymerase chain reaction. AMB Express. 2018;8:148. \u003c/li\u003e\n\u003cli\u003eAnejionu OCD, Nwilo PC, Ebinne ES. Long term assessment and mapping of erosion hotspots in southeastern Nigeria. In: Proceedings of FIG Working Week 2013 Environment for Sustainability; 2013 May 6\u0026ndash;10; Abuja, Nigeria. \u003c/li\u003e\n\u003cli\u003eAo T, Deb CR, Rao SR. Molecular strategies for identification and characterization of some wild edible mushrooms of Nagaland, India. Mol Biol Rep. 2019;47:621\u0026ndash;30. \u003c/li\u003e\n\u003cli\u003eApollos WP, Joshua VI, Musa HD, Gyang MS, Nyam DD. 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Front Microbiol. 2021;12:624347.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Plates","content":"\u003cp\u003ePlates 2 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Nigeria","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"mushrooms, DNA barcode, fungal, internal transcribed spacer (ITS), Zymo","lastPublishedDoi":"10.21203/rs.3.rs-9646588/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9646588/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMushrooms are grossly under exploited and efforts to domesticate them are not yielding enough results as over 95% of mushrooms consumed in Africa and most parts of the world are still collected from the wild. However, the utility of wild mushrooms has been hampered by incorrect morphological identifications. Molecular markers including the internal transcribed spacer (ITS) region are proven to be efficient in mushroom diversity studies. This research was aimed to investigate the diversity of wild mushrooms indigenous to southeast Nigeria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData description\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFifty (50) samples of wild growing mushrooms were collected using opportunistic sampling method in 5 states of the region. Zymo Research Quick-DNA Plant/Seed Miniprep kit was used for DNA extraction, the ITS region was amplified using PCR and subsequently sequenced with sanger sequencing technology. BLASTn search in Genbank databases were conducted to determine the identity of the sampled mushrooms, while the MEGA X software was used for evolutionary analysis. Genomic DNA was successfully extracted and amplified, although with varying band quality. Forty-one (41) out of the 50 mushroom samples were successfully sequenced and identified. The identified mushroom samples were classified into 11 families with family polyporaceae (13), Agaricaceae (9), Omphatotaceae (7) and Ganodermataceae (4), topping the list. \u003cem\u003eTrametes \u003c/em\u003e(7) and \u003cem\u003eLentinus\u003c/em\u003e (6) were the most abundant genera followed by \u003cem\u003eNeonothopanus\u003c/em\u003e(5), and \u003cem\u003eGanoderma \u003c/em\u003e(4). The phylogeny of the ITS gene of the 41 sequenced mushrooms divided the mushroom samples into 8 major clades, although formed a polytomy with clear multifurcations. Distinct clustering of the sampled mushrooms and its Genbank relatives was observed except for the case of sample 14. Barcode marker (ITS region) was effective in diversity studies of wild mushrooms of southeastern Nigeria.\u003c/p\u003e","manuscriptTitle":"Molecular Studies on the Diversity of Wild Mushrooms Indigenous to Southeastern Nigeria Using the Internal Transcribed Spacer (ITS) Region","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 10:56:11","doi":"10.21203/rs.3.rs-9646588/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f4547134-8c0e-4774-acc6-4d1b0810d047","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":67897431,"name":"Plant Molecular Biology and Genetics"}],"tags":[],"updatedAt":"2026-05-11T10:56:11+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 10:56:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9646588","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9646588","identity":"rs-9646588","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}