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Genome mining as a biotechnological tool for the discovery of
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novel biosynthetic genes in lichens
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Garima Singh1,2,*, Francesco Dal Grande1,2,3, Imke Schmitt1,2,4
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1 Senckenberg Biodiversity and Climate Research Centre (SBiK-F), 60325 Frankfurt am
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Main, Germany
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2 LOEWE Center for Translational Biodiversity Genomics (TBG), 60325 Frankfurt am Main,
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Germany
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3 Department of Biology, University of Padova, Via U. Bassi, 58/B, 35121 Padova, Italy
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4 Institute of Ecology, Diversity and Evolution, Goethe University, Frankfurt am Main,
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Germany
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Emails: Garima Singh: garima.singh@senckenberg.de, gsingh458@gmail.com
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Francesco Dal Grande: francesco.dalgrande@unipd.it
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Imke Schmitt: imke.schmitt@senckenberg.de
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*Corresponding author: Garima Singh
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Abstract
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The ever-increasing demand for novel drugs highlights the need for bioprospecting
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unexplored taxa for their biosynthetic potential. Lichen-forming fungi (LFF) are a rich source
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of natural products but their implementation in pharmaceutical industry is limited, mostly
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because the genes corresponding to a majority of their natural products is unknown.
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Furthermore, it is not known to what extent these genes encode structurally novel molecules.
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Advance in next-generation sequencing technologies has expanded the range of organisms
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that could be exploited for their biosynthetic potential. In this study, we mine the genomes of
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nine lichen-forming fungal species of the genus Umbilicaria for biosynthetic genes, and
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categorize the BGCs as “associated product structurally known”, and “associated product
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putatively novel”. We found that about 25-30% of the biosynthetic genes are divergent when
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compared to the global database of BGCs comprising of 1,200,000 characterized biosynthetic
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genes from planta, bacteria and fungi. Out of 217 total BGCs, 43 were only distantly related
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to known BGCs, suggesting they encode structurally and functionally unknown natural
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products. Clusters encoding the putatively novel metabolic diversity comprise PKSs (30),
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NRPSs (12) and terpenes (1). Our study emphasizes the utility of genomic data in
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bioprospecting microorganisms for their biosynthetic potential and in advancing the industrial
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application of unexplored taxa. We highlight the untapped structural metabolic diversity
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encoded in the lichenized fungal genomes. To the best of our knowledge, this is the first
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investigation identifying genes coding for NPs with potentially novel therapeutic properties in
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LFF.
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Key words
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Natural products, fungi, biosynthetic genes, lichen-forming fungi, secondary metabolites,
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drug discovery, medicinal fungi, BiG-FAM, BiG-SLiCE
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Background
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Natural products (NPs) are small molecules in nature produced by the organism. Historically,
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NPs have played a key role in drug discovery due to their broad pharmacological effects
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encompassing antimicrobial, antitumor, anti-inflammatory properties and against
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cardiovascular diseases [1,2]. In the past decades about 70% of the drugs were based on NPs
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or NP analogs [1,2]. The demand for novel drugs however, is ever increasing due to the
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emergence of antibiotic-resistant pathogens, the rise of new diseases, the existence of diseases
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for which no efficient treatments are available yet, and the need for replacement of drugs due
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to toxicity or high side-effects [3,4]. One way to address global health threats and to
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accelerate NP-based drug discovery efforts is bioprospecting unexplored taxa to assess their
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biosynthetic potential and identify potentially novel drug leads.
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Genes involved in the synthesis of a NPs are often grouped together in biosynthetic
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gene clusters [5–7]. These clusters have a core gene which codes for the backbone structure of
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the NP and other genes which may be involved in the modification of the backbone or may
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have a regulatory or transport-related function [5,8–10]. Depending upon the core gene, the
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BGCs could be grouped into the following major classes: non-ribosomal peptide synthetases
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(NRPS), polyketide synthases (PKS), NRPS-PKS (hybrid non-ribosomal peptide synthetase-
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polyketide synthase), terpenes, and RiPP (ribosomally synthesized and post-translationally
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modified peptide). Conserved motives, especially of the PKS genes, facilitate the
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bioinformatic detection of the clusters [11–14].
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Traditionally, a large portion of NP-based drugs have been contributed by a few
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organisms as the drug discovery was mostly restricted to culturable organisms [15–17]. In the
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last decades, bioinformatic prediction of biosynthetic gene or biosynthetic gene clusters
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(group of two or more genes that are clustered together and are involved in the production of
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a secondary metabolite) has revolutionized NP-based drug discovery as this process is
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culture-independent and enables rapid identification of entire biosynthetic landscape from so
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far unexplored NP resources, including silent or unexpressed genes. Two tools have been vital
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to bioinformatic approach to drug discovery: AntiSMASH [18] and MIBiG [19]. AntiSMASH
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includes one of the largest BGC database for BGC prediction [18] whereas MIBiG (Minimum
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Information about a Biosynthetic Gene Cluster) is a data repository allowing functional
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interpretation of target BGCs by comparison with BGCs with known functions [19]. Recently,
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efforts have been made to cluster homologous BGCs into gene cluster families (GCFs) and to
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simultaneously identify novel BGCs [20,21]. Two tools have been introduced to cluster BGCs
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into GCFs: BiG-FAM clusters structurally and functionally related BGCs into GCFs and
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identifies structurally most diverse BGCs by comparing the query BGCs to about 1,200,000
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BGCs of the BiG-FAM database [21]. BiG-SLiCE clusters homologous BGCs of a dataset
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into GCFs without reference to an external database, to identify unique BGCs in it [20].
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Bioinformatic prediction and clustering of BGCs allows rapid identification of potentially
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novel drug leads, reducing the costs and time associated with drug discovery by early
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elimination of unlikely candidates.
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Lichens, symbiotic organisms composed of fungal and photosynthetic partners (green
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algae or cyanobacteria, or both), are suggested to be treasure chests of biosynthetic genes and
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NPs [22–24]. Although the number of identified NPs per LFF is typically less than 5 [25], the
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number of BGCs in the genomes of LFF may range from 25-60 [12]. It is not well known
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how BGCs from LFF relate in structure and function to BGCs from bacteria and non-
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lichenized fungi, i.e., if a portion of the BGC landscape of LFF is distinct, and might serve as
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a source of NPs with novel therapeutic properties. Difficulties associated with heterologous
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expression of LFF genes have so far restricted the application of LFF-derived NPs in the
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industry. Recently two biosynthetic genes from LFF have been successfully heterologously
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expressed [9,26]. This, combined with advances in long-read sequencing technology (higher
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genome quality), and low cost of sequencing provide a promising way forward to discover
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LFF-derived NPs with pharmacological potential.
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Here we employ a long-read sequencing based comparative genomics and genome
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mining approach to estimate the BGC functional diversity of nine species of the lichenized
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fungal genus Umbilicaria. Specifically, we aim to answer the following questions: (1) What is
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the functional diversity of BGCs in Umbilicaria? and 2) what is the percentage of novel
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BGCs and species-specific BGCs in Umbilicaria?
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Results
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Overview of BGCs in the Umbilicaria genomes
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Umbilicaria genomes contain 20-33 BGCs, with the highest number of BGCs detected in U.
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deusta and lowest in U. phaea (Fig. 1A). We did not observe a correlation between genome
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size and number of BGCs (correlation coefficient = 0.10). Umbilicaria species contain an
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average of 13 PKS clusters, and 4.2 NRPS clusters per species (Fig. 1B), making a PKS to
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NRPS clusters proportion of 3.1). The most dominant class of BGC in Umbilicaria are the
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ones with PKSs, amounting more than 50% of the total BGCs, followed by terpene clusters
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(about 20%) and NRPS clusters (about 15%) respectively, (Fig. 2A). In contrast, NRPSs are
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the most dominant class among fungal and bacterial BGCs (Fig. 2B, C), amounting to about
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42% and 30% respectively.
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Fig 1. Genome quality metrics and diversity of biosynthetic genes in nine species of Umbilicaria. A)
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Genome metrics including the total number of biosynthetic gene clusters as predicted by antiSMASH,
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and number of genes and proteins estimated by InterProScan and SignalP as implemented in the
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funannotate pipeline. B) Diversity of biosynthetic gene clusters associated with major natural product
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categories, indicated as percentages (colored bars) and absolute numbers (numbers on bars).
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Fig 2. Biosynthetic gene clusters in A) Umbilicaria, B) the full fungal BGC dataset and C) full
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bacterial BGC dataset. PKSs are the most dominant class of BGCs in Umbilicaria whereas in fungi
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and bacteria NRPSs are the predominant BGC class. Although the publicly available LFF genomes (>
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50) are much lower than the non-lichenized fungi (about 2100), all the LFF genomes analyzed for
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their BGCs have PKSs as the most common class of BGCs (see discussion for details), suggesting that
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the predominance of PKSs as observed here in Umbilicaria dataset is a common feature of LFF
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genomes.
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Species
total BGCs
Genome size
Completeness
Scaffolds
#genes
#proteins
U. deusta
33
40.9
97.6
44
8,949
8,857
U. freyi
23
47.5
95.7
107
10,156
10.065
U. grisea
20
44.43
96.9
38
8,155
8,104
U. hispanica
25
48.6
97.3
53
8,781
8,696
U. muhlenbergii
23
34.81
100
7
8,968
8,854
U. phaea
19
35.1
97.2
38
7,681
7,628
U. pustulata
27
35.7
96.8
27
8,790
8,740
U. spodochroa
27
44.3
97.6
130
8,791
8,705
U. subpolyphylla
20
31.8
97.6
39
8,556
8,410
A
B
U. deusta
U. freyi
U. grisea
U. hispanica
U. muhlenbergii
U. phaea
U. pustulata
U. spodochroa
U. subpolyphylla
20 %
40 %
60 %
80 %
100 %
PKS
terpene
NRPS
other
RiPP
3
21
9
10
13
15
11
15
13
10
4
6
3
6
2
3
6
5
5
4
1
3
5
5
4
5
5
4
5
3
2
1
2
4
2
2
0.5 %
9.5 %
17.2 %
19.0 %
53.8 %
Biosynthetic genes
in Umbilicaria
Species 9
Total BGCs 217
0.6 %
7.1 %
42.6 %
17.6 %
32.1 %
PKS terpene NRPS Other RiPP
Biosynthetic
genes in fungi
24.1 %
21.7 %
29.5 %
7.8 %
16.9 %
Biosynthetic
genes in bacteria
Species 2171
Total BGCs 124092
Species 18661
Total BGCs 1096473
A B C
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BGC clustering: BiG-FAM
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Of the total 217 BGCs found in 9 Umbilicaria species, 18 BGCs (8%) obtained a BGC-to-
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GCFs (Gene Cluster Families) pairing distance lower than 400, indicating that they
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potentially code for structurally very similar compounds known from the BGCs of their
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respective GCFs (Fig. 3A, B); 156 (71%) had a pairing distance of 400-900, suggesting that
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they share similar domain architectures with previously described BGCs in the BiG-FAM
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database. We identify the clusters belonging to above two groups as “associated product
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structurally known”. 43 BGCs (21%) had a pairing distance greater than 900 and are
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potentially BGCs encoding novel natural products (Fig. 3 A). We identify these clusters as
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“associated product putatively novel”. These BGCs belong to the class terpenes (1 BGCs),
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NRPSs (12 BGCs) and PKSs (30 BGCs). The details of these BGCs and the sequence of the
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core gene is provided in the Additional file 1.
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Within-genus comparison of BGCs: BiG-SLiCE
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We identified species-specific BGCs within Umbilicaria using BiG-SLiCE. Out of 217 total
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BGCs, 159 (72%) grouped into 20 GCFs (d=900), suggesting they are similar clusters shared
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by multiple species, while 58 (28%) had a d > 900, indicating that they were only distantly
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related to other BGCs in Umbilicaria. Each Umbilicaria species contains four to ten (6.45 –
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16.13%) unique, species-specific BGCs (Additional file 2A). In U. deusta we detected two
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BGCs (both with PKSs) that were extremely divergent (d > 1800) within the genus
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(Additional file 2B).
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Out of these BGCs, 15 are unique within Umbilicaria as well divergent from the
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BGCs to the known BGCs present in BiG-FAM database.
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Fig. 3 A) Total BGCs in Umbilicaria and GCFs as identified by BiG-FAM and the number of BGCs
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clustering into a pre-characterized gene cluster families (GCFs) in BiG-FAM and their distance
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groups. d<=400 suggest that the cluster codes for a structurally and functionally similar NP, d=400-
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900 indicates that the BGC codes for a related but structurally and functionally divergent NP, whereas
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d>900 suggests that the BGC codes for a novel NP. B) Bar plots representing the percentage of BGCs
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in each Umbilicaria species with d<= 400, d= 400-900 and d>900. Only a small proportion of BGCs
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in each species could be grouped into a pre-characterized GCF in the BiG-FAM database (21,678
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species, 1,225,071 BGCs and 29,955 GCFs), whereas a large proportion of them is only distantly
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related to the pre-characterized BGCs. About 15-30% of BGCs could not be grouped into BiG-FAM
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gene cluster families and potentially code of structurally and functionally divergent NPs.
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163
U. deusta
U. freyi
U. grisea
U. hispanica
U. muhlenbergii
U. phaea
U. pustulata
U. spodochroa
U. subpolyphylla
20 %
40 %
60 %
80 %
100 %
T<=400 T=400-900 T>900
Species
BGCs
GCFs
d<=400
d=400-900
d>900
U. deusta
33
26
1
26
6
U. freyi
23
15
3
17
3
U. grisea
20
13
2
15
3
U. hispanica
25
18
2
19
4
U. muhlenbergii
23
19
2
14
7
U. phaea
19
11
1
14
4
U. pustulata
27
17
2
20
5
U. spodochroa
27
19
4
19
4
U. subpolyphylla
20
13
1
12
7
total
217
135
18
156
43
A
B
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164
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Discussion
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Lichens produce a large number of natural products, and they have even more BGCs [27–29].
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However, whether these BGCs encode hitherto unknown metabolic diversity/chemical
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structures is not known. Here we quantify, for the first time, the proportion of BGCs linked to
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putatively novel natural products in a group of closely related lichen-forming fungi. The
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identification of 23 clusters encoding putatively novel chemical structures can be useful in the
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search for new structures and drug leads.
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In this study we mined the genomes of the Umbilicaria spp. to identify all the BGCs
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(Fig. 1), followed by clustering the structurally and functionally similar BGCs into gene
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cluster families (Fig. 3A, B) and identifying the gene clusters potentially coding for novel
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NPs (Fig. 4, Additional File 1). Using Umbilicaria spp. as a study system, we show that LFF
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biosynthetic landscape is diverse from that of non-lichenized fungi and bacteria, being
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particularly rich in PKSs (Fig 2) and that a substantial portion for LFF BGCs (about 28% in
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case of Umbilicaria) potentially codes for novel NPs (Fig. 3A, B). To the best of our
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knowledge, this is the first investigation of this kind, implementing state of the art
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computational tools to determines the proportion of metabolic diversity in LFF coding for
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U. hispannica
6.45 %
U. phaea
8.06 %
U. subpolyphylla
8.06 %
U. grisea
8.06 %
U. pustulata
11.29 %
U. muehlenbergii
12.90 %
U. spodochroa
12.90 %
U. freyi
16.13 %
U. deusta
16.13 %
Species 9
Total BGCs 217
Total novel BGCs 58
novel BGCs/species 6.5
Novel terpenes 33
Novel PKSs 24
Novel NRPS 1
Fig. 4 Pie chart depicting the contribution
of each species to the overall novel
Umbilicaria BGCs (as identified by BiG-
SLiCE, T>900) Each Umbilicaria species
contains about 4-10 unique, species-
specific BGCs. U. freyi and U. deusta
contain the highest number of novel
BGCs. The number of novel BGCs
slightly positively correlated to the
number of clusters (R=0.68). Out of 58
BGCs unique BGCs (T>900) 56.89%
were terpene- and 41.37% were PKS
clusters.
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novel drugs and identifying candidate genes as a source of drug leads to prioritize them for
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drug discovery efforts.
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Biosynthetic potential and BGC diversity of Umbilicaria spp.
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Although only PKSs-derived NPs are reported from Umbilicaria species (gyrophoric-,
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umbilicaric-, and hiascic acid etc.) [30–32], we found that the Umbilicaria BGC landscape is
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biosynthetically diverse and comprises three to five classes of NPs (Fig 1A, B). This is also
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the case for most other LFF, for instance, PKS-derived NPs, are reported from Bacidia spp.,
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Cladonia spp., Endocarpon spp., Evernia prunastri, Umbilicaria pustulata, Pseudevernia
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furfuracea, but all of them contain several PKS, NRPS and terpene gene clusters [12,29,32–
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34]. All these above-stated studies show that the biosynthetic potential of LFF vastly exceeds
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their detectable chemical diversity. On average LFF may contain up to 30-40 BGCs but the
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number of identified compounds per species is usually less than 10 [12,33,35]. This could be
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because most of the clusters are silent and do not synthesize the NP or it could be simply
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because of the failure to detect the NP. Bioinformatic characterization of entire BGC
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landscape followed by identification of most distinct BGCs provides a way to estimate the
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novelty of all the BGCs including the unexpressed and silent ones.
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BGC diversity of LFF as compared to bacteria and non-lichenized fungi
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We identified five classes of BGCs in the Umbilicaria genomes. PKSs were the most
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dominant class, amounting to about 50%, followed by terpenes (19%), and NRPSs (14%)
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(Fig. 1, Fig. 2 A). BGCs including PKSs typically make up the majority of BGCs in LFF:
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Evernia prunastri (60%), Pseudevernia furfuracea (61%), Cladonia spp. (65%), Endocarpon
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pusillum (58%), Lobaria pulmonaria (46%), and Ramalina peruviana (63%) (cite).
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Although the number of publicly accessible, good quality LFF genomes are rather
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scarce for LFF (<25) as compared to the bacteria and non-lichenized fungi, the data available
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(9 Umbilicaria spp. genomes [36] plus 9 other publicly available lichen genomes) suggests
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that the predominance of PKSs is a common feature of BGCs in LFF contributing more than
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50% to the total BGCs. In contrast, in bacteria and non-lichenized fungi, NRPS are the most
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prevalent BGC class, amounting to about 30% and 42% respectively, followed by the PKSs
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(Fig. 2 B, C). This suggests that the biosynthetic potential of LFF is unique as compared to
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the other organisms traditionally exploited for NPs, i.e., non-lichenized fungi and bacteria,
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especially with respect to PKS diversity. In this regard, a recent study suggested that although
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bacteria and fungi may share a few NPs, they do not have an overlapping chemical space and
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instead have distinct biosynthetic potential [37]. LFF having a distinct BGC landscape
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presents a complementary resource of NPs with promising medicinally-relevant biosynthetic
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properties.
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Umbilicaria BGCs: Gene Cluster Families (GCFs) and novel NPs
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Gene cluster families (GCFs) are the groups of BGCs that encode the same or very similar
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molecules. A total of 217 BGCs from nine Umbilicaria species were clustered into of 135
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unique GCFs. (Fig 3 A) This suggests that Umbilicaria spp. are potentially capable of
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synthesizing many structurally and functionally different natural products, although in nature
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only one compound class is typically detected (depsides, linked to a BGC containing a PKS).
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Only a small fraction of Umbilicaria BGCs, 8%, could be clustered with the pre-
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characterized BGCs (Fig. 3A, B). About 71% of the BGCs were clustered to the BiG-FAM
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GCFs with d= 400-900, indicating that they were only distantly related in structure and
228
function (Fig. 3 A, B). These BGCs are also interesting candidates to be investigated for their
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biosynthetic properties as even a minor difference in the cluster and the chemistry of the final
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metabolites could cause a crucial difference in bioactivity related to function and the
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pharmacological potential of the product [38].
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About 21% percent BGCs were highly divergent (d>900) and are novel, potentially
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coding for structurally and functionally unique NPs and could be an interesting target for NP-
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based drug discovery (Fig. 3 B). The strikingly high number of novel BGCs in a fungal genus
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adds to the mounting evidence that the non-model and understudied taxa are enormous,
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untapped source of novel NPs.
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Genome mining for large genomic regions, such as fungal BGCs, works best when the
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genomes under study are highly complete and contiguous, as well as reliably annotated. Many
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publicly available LFF genomes do not fulfill these criteria, preventing a taxonomically broad
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study of biosynthetic novelty encoded in the genomes of LFF. We were surprised that even a
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“chemically boring” lichen taxon, such as the genus Umbilicaria, harbored 43 BGCs
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encoding putatively unknown natural product diversity. It lets us suspect that chemically more
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diverse taxa, e.g. Lecanorales or Pertusariales, each including hundreds of species, are even
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richer sources of BGCs with novel functions, and compounds with potential pharmaceutical
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applications. Increased genome sequencing of taxonomically diverse LFF, combined with
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higher genome qualities will facilitate BGC discovery.
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Unique BGCs within Umbilicaria spp.: BiG-SLiCE
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BGCs which are uniquely occurring in a species are candidates for interesting NPs [20,37,39].
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On average each Umbilicaria species contains seven species-specific BGCs. Most of the
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novel BGCs are present in U. deusta and U. freyi whereas U. hispanica has lowest number of
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novel BGCs (Fig. 4). This suggests that even closely related species (species within a single
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genus) contain diverse biosynthetic potential. Species or strain specific biosynthetic potential
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has already been demonstrated for LFF, for example in Umbilicaria pustulata [32] and
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Pseudevernia furfuracea [33] and it is a rather common occurrence in fungi [32,37,40]. For
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instance, majority of the BGCs in Streptomyces, i.e., 57% have been shown to be strain-
257
specific [41]. The unique BGCs within Umbilicaria belong to the BGC classes PKSs,
258
terpenes, NRPS as well as to indoles (Supplementary information S2). Of these, mostly only
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PKS derived NPs have been well studies in LFF and shown to have diverse pharmacological
260
properties [42–44].
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Two PKS obtained a pairing distance greater than 1800. These were the most
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divergent BGCs (Supplementary information S2) within Umbilicaria and were “orphan
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BGCs”, i.e., for these clusters the corresponding metabolite cannot be predicted. Recently
264
several orphan clusters have been activated to synthesize a compound with useful
265
pharmacological properties, for example the antibiotic holomycin gene cluster from the
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marine bacterium Photobacterium galatheae was activated in culture [45–48]. The novel and
267
orphan clusters reported in this study are potentially interesting candidates for synthesizing
268
molecules with unique pharmacological properties and may serve as drugs leads.
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About 17% of fungal BGCs, 8% of bacterial BGCs and 19% of LFF BGCs comprise
270
terpenes (Fig. 2). Terpenes are pharmaceutically extremely versatile, with antimicrobial, anti-
271
inflammatory, neurodegenerative, and cytotoxic properties [49–54]. Some of the common
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plant-derived terpenes and terpenoids are curcumin, Eucalyptus oil. Although several studies
273
reported pharmacological properties of fungal terpenes, such studies on LFF are missing
274
despite the slightly larger proportion of terpenes in LFF genomes. In this study we report
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structurally and functionally unique terpenes as promising candidates, to be investigated for
276
their pharmaceutical potential.
277
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14
Conclusion
279
In this study we identified the biosynthetic diversity of the lichen forming fungal genus
280
Umbilicaria, grouped the structurally and functionally related clusters into GCFs and
281
identified the most diverse, potentially novel clusters. Using Umbilicaria as model system we
282
show that LFF constitute a valuable source of novel NPs suggesting that there is tremendous
283
natural product diversity to be discovered in them. In particular they are rich source of novel
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PKSs and terpenes. Combining this observation with other sequenced LFF we show that LFF
285
are indeed a source of untapped natural product diversity.
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Materials and methods
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Dataset
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The genomes of the following Umbilicaria species were used for this study: U. deusta, U.
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freyi, U. grisea, U. subpolyphylla, U. hispanica, U. phaea, U. pustulata, U. muhlenbergii and
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U. spodochroa. Except U. muhlenbergii which belongs to the Bioproject PRJNA239196, all
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the other genomes are a part of Bioproject PRJNA820300 (Table 1). The details of sample
293
and library preparation, as well as genome sequencing for U. muhlenbergii are available in
294
Park et al. [55] and for the other eight Umbilicaria spp in Singh et al. [36]. Briefly, all the
295
genomes except U. muhlenbergii were generated via PacBio SMRT sequencing on the Sequel
296
System II using the continuous long read (CLR) mode or the circular consensus sequencing
297
(CCS) mode. The continuous long reads (i.e. CLR reads) were then processed into highly
298
accurate consensus sequences (i.e. HiFi reads) and assembled into contigs using the assembler
299
metaFlye v2.7 [56]. The contigs were then scaffolded with LRScaf v1.1.12
300
(github.com/shingocat/lrscaf, [57]). We used only binned Ascomyocta reads for this study
301
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15
(extracted using blastx in DIAMOND (--more-sensitive --frameshift 15 –range-culling) on a
302
custom database and following the MEGAN6 Community Edition pipeline [58]).
303
304
BGC prediction and clustering: AntiSMASH
305
BGCs were predicted using antiSMASH (antibiotics & SM Analysis Shell, v6.0) with scripts
306
implemented in the funannotate pipeline [18,59]. We tested, if a smaller genome size was
307
correlated with a lower number of BGCs. A correlation coefficient near 0 indicates no
308
correlation whereas a coefficient near 1 indicates a positive correlation.
309
310
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BGC clustering into BiG-FAM GCFs
312
The homologous BGCs present in the Umbilicaria genomes were grouped into Gene Cluster
313
Families (GCFs) using BiG-FAM, which clusters structurally and functionally related BGCs
314
into GCFs and identifies the structurally most diverse BGCs by comparing the query BGCs to
315
the 1,225,071 BGCs of the BiG-FAM database. The 1,225,071 BGCs in BiG-FAM are
316
Table 1. Voucher information of the genomes used in the study
Organism
Sample ID
Sequencing
technology
BioProject
BioSample
Genome accession
Umbilicaria deusta
TBG_2334
PacBio sequal II
PRJNA820300
SAMN26992774
JALILR000000000
Umbilicaria freyi
TBG_2329
PacBio sequal II
PRJNA820300
SAMN26992773
JALILQ000000000
Umbilicaria grisea
TBG_2336
PacBio sequal II
PRJNA820300
SAMN26992780
JALILX000000000
Umbilicaria hispanica
TBG_2337
PacBio sequal II
PRJNA820300
SAMN26992775
JALILS000000000
Umbilicaria muhlenbergii
KoLRI No. LF000956
Illumina HiSeq
PRJNA239196
SAMN02650300
GCA_000611775.1
Umbilicaria phaea
TBG_1112
PacBio sequal II
PRJNA820300
SAMN26992776
JALILT000000000
Umbilicaria pustulata
TBG_2345
PacBio sequal II
PRJNA820300
SAMN26992777
JALILU000000000
Umbilicaria spodochroa
TBG_2434
PacBio sequal II
PRJNA820300
SAMN26992778
JALILV000000000
Umbilicaria subpolyphylla
TBG_2324
PacBio sequal II
PRJNA820300
SAMN26992779
JALILW000000000
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16
clustered into 29,955 GCFs based on similar domain architectures. A GCF comprises closely
317
related BGCs, potentially encoding the same or very similar compounds. By enabling such
318
clustering BiG-FAM establishes the degree of similarity of BGCs of a query taxon to
319
currently known (functionally pre-characterized) fungal and bacterial BGCs. The antiSMASH
320
job ID of each Umbilicaria species was used as input for BiG-FAM analysis.
321
322
Quantification of BGC diversity and species specific BGCs in Umbilicaria: BiG-SLiCE
323
We used BiG-SLiCE [20] to identify the most unique or species-specific BGCs within
324
Umbilicaria. While BiG-FAM identifies the most diverse BGCs compared to pre-
325
characterized BGCs from other taxa deposited in public repositories, BiG-SLiCE 1.1.0. is a
326
networking-based tool which assesses relations of BGCs of the dataset (i.e., Umbilicaria
327
BGCs in our study) and estimates their distance within the dataset to identity unique, species-
328
specific BGCs. The resulting distance indicates how closely a given BGC is related to other
329
BGCs. BiG-SLiCE was run on the Umbilicaria BGC dataset (i.e., 217 BGCs from nine
330
Umbilicaria spp.) using three different thresholds: 400, 900 and 1800.
331
332
Declarations
333
Ethics approval and consent to participate: Not applicable
334
Consent for publication: Not applicable
335
Availability of data and materials:
336
The dataset(s) supporting the conclusions of this article are available in the GenBank
337
repository, accession PRJNA820300, under the accession numbers JALILQ000000000 -
338
JALILY000000000. The lichen samples of the corresponding Umbilicaria Spp. are available
339
as Biosamples SAMN27294873 - SAMN27294881 and the mycobiont samples as
340
.CC-BY-ND 4.0 International licensemade available under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted May 4, 2022. ; https://doi.org/10.1101/2022.05.04.490581doi: bioRxiv preprint
17
Biosamples SAMN26992773 - SAMN26992781. The antiSMASH files of Umbilicaria spp.
341
is available at figshare (doi: 10.6084/m9.figshare.19625997).
342
Competing interests: None
343
Funding: This research was funded by LOEWE-Centre TBG, funded by the Hessen
344
State Ministry of Higher Education, Research and the Arts (HMWK).
345
Authors' contributions:
346
GS analyzed and interpreted the data, generated the figures and tables and wrote the
347
manuscript.
348
FDG analyzed the data and assisted with the bioinformatic parts of the study.
349
IS interpreted the data, co-prepared the figures and co-wrote the manuscript.
350
All authors read and approved the final manuscript.
351
Acknowledgements
352
We thank Prof. Marnix Medema and Dr. Satria Kautsar for their support with BiG-SLiCE
353
program.
354
355
Supporting Information
356
S1 Most divergent BGCs in Umbilicaria as identified by BiG-FAM, along with the cluster
357
information and sequence.
358
S2 Most distantly related BGCs within Umbilicaria as identified by BiG-SLiCE along with
359
the cluster information.
360
361
362
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
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18
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