A structural variant at ASIP associated with the darkness of hair coat is found in multiple zebu cattle populations.

A structural variant (SV) in the agouti signaling protein gene (ASIP), namely ASIP-SV1, has been found to strongly correlate with the darkness of hair coat in specific regions of the body of bulls from the zebu (Bos indicus) Nellore breed. Here we visually analyzed the whole-genome sequence of zebu and taurine (Bos taurus) cattle to elucidate the extent of spread of ASIP-SV1 in different cattle populations. Of 216 sequences analyzed, 63 zebu (45.9%) and five taurine (6.3%) animals had at least one copy of ASIP-SV1. Four of the taurine animals presenting the SV were Romagnola cattle, a breed with history of zebu introgression. The remaining taurine animal was a Simmental, a breed frequently used in crossbreeding. These data provide evidence that ASIP-SV1 is commonly found in zebu populations, in addition to taurine animals with zebu admixture.

Geographical contrasts of Y-chromosomal haplogroups from wild and domestic goats reveal ancient migrations and recent introgressions.

By their paternal transmission, Y-chromosomal haplotypes are sensitive markers of population history and male-mediated introgression. Previous studies identified biallelic single-nucleotide variants in the SRY, ZFY and DDX3Y genes, which in domestic goats identified four major Y-chromosomal haplotypes, Y1A, Y1B, Y2A and Y2B, with a marked geographical partitioning. Here, we extracted goat Y-chromosomal variants from whole-genome sequences of 386 domestic goats (75 breeds) and seven wild goat species, which were generated by the VarGoats goat genome project. Phylogenetic analyses indicated domestic haplogroups corresponding to Y1B, Y2A and Y2B, respectively, whereas Y1A is split into Y1AA and Y1AB. All five haplogroups were detected in 26 ancient DNA samples from southeast Europe or Asia. Haplotypes from present-day bezoars are not shared with domestic goats and are attached to deep nodes of the trees and networks. Haplogroup distributions for 186 domestic breeds indicate ancient paternal population bottlenecks and expansions during migrations into northern Europe, eastern and southern Asia, and Africa south of the Sahara. In addition, sharing of haplogroups indicates male-mediated introgressions, most notably an early gene flow from Asian goats into Madagascar and the crossbreeding that in the 19th century resulted in the popular Boer and Anglo-Nubian breeds. More recent introgressions are those from European goats into the native Korean goat population and from Boer goat into Uganda, Kenya, Tanzania, Malawi and Zimbabwe. This study illustrates the power of the Y-chromosomal variants for reconstructing the history of domestic species with a wide geographical range.

Variants at the ASIP locus contribute to coat color darkening in Nellore cattle.

BACKGROUND: Nellore cattle (Bos indicus) are well-known for their adaptation to warm and humid environments. Hair length and coat color may impact heat tolerance. The Nellore breed has been strongly selected for white coat, but bulls generally exhibit darker hair ranging from light grey to black on the head, neck, hump, and knees. Given the potential contribution of coat color variation to the adaptation of cattle populations to tropical and sub-tropical environments, our aim was to map positional and functional candidate genetic variants associated with darkness of hair coat (DHC) in Nellore bulls. RESULTS: We performed a genome-wide association study (GWAS) for DHC using data from 432 Nellore bulls that were genotyped for more than 777 k single nucleotide polymorphism (SNP) markers. A single major association signal was detected in the vicinity of the agouti signaling protein gene (ASIP). The analysis of whole-genome sequence (WGS) data from 21 bulls revealed functional variants that are associated with DHC, including a structural rearrangement involving ASIP (ASIP-SV1). We further characterized this structural variant using Oxford Nanopore sequencing data from 13 Australian Brahman heifers, which share ancestry with Nellore cattle; we found that this variant originates from a 1155-bp deletion followed by an insertion of a transposable element of more than 150 bp that may impact the recruitment of ASIP non-coding exons. CONCLUSIONS: Our results indicate that the variant ASIP sequence causes darker coat pigmentation on specific parts of the body, most likely through a decreased expression of ASIP and consequently an increased production of eumelanin.

Transcriptomic Characterization of Cow, Donkey and Goat Milk Extracellular Vesicles Reveals Their Anti-Inflammatory and Immunomodulatory Potential.

Milk extracellular vesicles (mEVs) seem to be one of the main maternal messages delivery systems. Extracellular vesicles (EVs) are micro/nano-sized membrane-bound structures enclosing signaling molecules and thus acting as signal mediators between distant cells and/or tissues, exerting biological effects such as immune modulation and pro-regenerative activity. Milk is also a unique, scalable, and reliable source of EVs. Our aim was to characterize the RNA content of cow, donkey, and goat mEVs through transcriptomic analysis of mRNA and small RNA libraries. Over 10,000 transcripts and 2000 small RNAs were expressed in mEVs of each species. Among the most represented transcripts, 110 mRNAs were common between the species with cow acting as the most divergent. The most represented small RNA class was miRNA in all the species, with 10 shared miRNAs having high impact on the immune regulatory function. Functional analysis for the most abundant mRNAs shows epigenetic functions such as histone modification, telomere maintenance, and chromatin remodeling for cow; lipid catabolism, oxidative stress, and vitamin metabolism for donkey; and terms related to chemokine receptor interaction, leukocytes migration, and transcriptional regulation in response to stress for goat. For miRNA targets, shared terms emerged as the main functions for all the species: immunity modulation, protein synthesis, cellular cycle regulation, transmembrane exchanges, and ion channels. Moreover, donkey and goat showed additional terms related to epigenetic modification and DNA maintenance. Our results showed a potential mEVs immune regulatory purpose through their RNA cargo, although in vivo validation studies are necessary.

PANEV: an R package for a pathway-based network visualization.

BACKGROUND: During the last decade, with the aim to solve the challenge of post-genomic and transcriptomic data mining, a plethora of tools have been developed to create, edit and analyze metabolic pathways. In particular, when a complex phenomenon is considered, the creation of a network of multiple interconnected pathways of interest could be useful to investigate the underlying biology and ultimately identify functional candidate genes affecting the trait under investigation. RESULTS: PANEV (PAthway NEtwork Visualizer) is an R package set for gene/pathway-based network visualization. Based on information available on KEGG, it visualizes genes within a network of multiple levels (from 1 to n) of interconnected upstream and downstream pathways. The network graph visualization helps to interpret functional profiles of a cluster of genes. CONCLUSIONS: The suite has no species constraints and it is ready to analyze genomic or transcriptomic outcomes. Users need to supply the list of candidate genes, specify the target pathway(s) and the number of interconnected downstream and upstream pathways (levels) required for the investigation. The package is available at https://github.com/vpalombo/PANEV.

Signatures of selection and environmental adaptation across the goat genome post-domestication.

BACKGROUND: Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip. These animals were partitioned into groups based on geographical area, production uses, available records on solid coat color and environmental variables including the sampling geographical coordinates, to investigate the role of natural and/or artificial selection in shaping the genome of goat breeds. RESULTS: Several signatures of selection on different chromosomal regions were detected across the different breeds, sub-geographical clusters, phenotypic and climatic groups. These regions contain genes that are involved in important biological processes, such as milk-, meat- or fiber-related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences. Our results confirm previous findings in other species on adaptation to extreme environments and human purposes and provide new genes that could explain some of the differences between goat breeds according to their geographical distribution and adaptation to different environments. CONCLUSIONS: These analyses of signatures of selection provide a comprehensive first picture of the global domestication process and adaptation of goat breeds and highlight possible genes that may have contributed to the differentiation of this species worldwide.

Genome-wide SNP profiling of worldwide goat populations reveals strong partitioning of diversity and highlights post-domestication migration routes.

BACKGROUND: Goat populations that are characterized within the AdaptMap project cover a large part of the worldwide distribution of this species and provide the opportunity to assess their diversity at a global scale. We analysed genome-wide 50 K single nucleotide polymorphism (SNP) data from 144 populations to describe the global patterns of molecular variation, compare them to those observed in other livestock species, and identify the drivers that led to the current distribution of goats. RESULTS: A high degree of genetic variability exists among the goat populations studied. Our results highlight a strong partitioning of molecular diversity between and within continents. Three major gene pools correspond to goats from Europe, Africa and West Asia. Dissection of sub-structures disclosed regional gene pools, which reflect the main post-domestication migration routes. We also identified several exchanges, mainly in African populations, and which often involve admixed and cosmopolitan breeds. Extensive gene flow has taken place within specific areas (e.g., south Europe, Morocco and Mali-Burkina Faso-Nigeria), whereas elsewhere isolation due to geographical barriers (e.g., seas or mountains) or human management has decreased local gene flows. CONCLUSIONS: After domestication in the Fertile Crescent in the early Neolithic era (ca. 12,000 YBP), domestic goats that already carried differentiated gene pools spread to Europe, Africa and Asia. The spread of these populations determined the major genomic background of the continental populations, which currently have a more marked subdivision than that observed in other ruminant livestock species. Subsequently, further diversification occurred at the regional level due to geographical and reproductive isolation, which was accompanied by additional migrations and/or importations, the traces of which are still detectable today. The effects of breed formation were clearly detected, particularly in Central and North Europe. Overall, our results highlight a remarkable diversity that occurs at the global scale and is locally partitioned and often affected by introgression from cosmopolitan breeds. These findings support the importance of long-term preservation of goat diversity, and provide a useful framework for investigating adaptive introgression, directing genetic improvement and choosing breeding targets.

GHap: an R package for genome-wide haplotyping.

UNLABELLED: The GHap R package was designed to call haplotypes from phased marker data. Given user-defined haplotype blocks (HapBlock), the package identifies the different haplotype alleles (HapAllele) present in the data and scores sample haplotype allele genotypes (HapGenotype) based on HapAllele dose (i.e. 0, 1 or 2 copies). The output is not only useful for analyses that can handle multi-allelic markers, but is also conveniently formatted for existing pipelines intended for bi-allelic markers. AVAILABILITY AND IMPLEMENTATION: https://cran.r-project.org/package=GHap CONTACT: ytutsunomiya@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Revealing misassembled segments in the bovine reference genome by high resolution linkage disequilibrium scan.

BACKGROUND: Misassembly signatures, created by shuffling the order of sequences while assembling a genome, can be detected by the unexpected behavior of marker linkage disequilibrium (LD) decay. We developed a heuristic process to identify misassembly signatures, applied it to the bovine reference genome assembly (UMDv3.1) and presented the consequences of misassemblies in two case studies. RESULTS: We identified 2,906 single nucleotide polymorphism (SNP) markers presenting unexpected LD decay behavior in 626 putative misassembled contigs, which comprised less than 1 % of the whole genome. Although this represents a small fraction of the reference sequence, these poorly assembled segments can lead to severe implications to local genome context. For instance, we showed that one of the misassembled regions mapped to the POLL locus, which affected the annotation of positional candidate genes in a GWAS case study for polledness in Nellore (Bos indicus beef cattle). Additionally, we found that poorly performing markers in imputation mapped to putative misassembled regions, and that correction of marker positions based on LD was capable to recover imputation accuracy. CONCLUSIONS: This heuristic approach can be useful to cross validate reference assemblies and to filter out markers located at low confidence genomic regions before conducting downstream analyses.

Relative extended haplotype homozygosity signals across breeds reveal dairy and beef specific signatures of selection.

BACKGROUND: A number of methods are available to scan a genome for selection signatures by evaluating patterns of diversity within and between breeds. Among these, "extended haplotype homozygosity" (EHH) is a reliable approach to detect genome regions under recent selective pressure. The objective of this study was to use this approach to identify regions that are under recent positive selection and shared by the most representative Italian dairy and beef cattle breeds. RESULTS: A total of 3220 animals from Italian Holstein (2179), Italian Brown (775), Simmental (493), Marchigiana (485) and Piedmontese (379) breeds were genotyped with the Illumina BovineSNP50 BeadChip v.1. After standard quality control procedures, genotypes were phased and core haplotypes were identified. The decay of linkage disequilibrium (LD) for each core haplotype was assessed by measuring the EHH. Since accurate estimates of local recombination rates were not available, relative EHH (rEHH) was calculated for each core haplotype. Genomic regions that carry frequent core haplotypes and with significant rEHH values were considered as candidates for recent positive selection. Candidate regions were aligned across to identify signals shared by dairy or beef cattle breeds. Overall, 82 and 87 common regions were detected among dairy and beef cattle breeds, respectively. Bioinformatic analysis identified 244 and 232 genes in these common genomic regions. Gene annotation and pathway analysis showed that these genes are involved in molecular functions that are biologically related to milk or meat production. CONCLUSIONS: Our results suggest that a multi-breed approach can lead to the identification of genomic signatures in breeds of cattle that are selected for the same production goal and thus to the localisation of genomic regions of interest in dairy and beef production.

Genetic diversity of Italian goat breeds assessed with a medium-density SNP chip.

BACKGROUND: Among the European countries, Italy counts the largest number of local goat breeds. Thanks to the recent availability of a medium-density SNP (single nucleotide polymorphism) chip for goat, the genetic diversity of Italian goat populations was characterized by genotyping samples from 14 Italian goat breeds that originate from different geographical areas with more than 50 000 SNPs evenly distributed on the genome. RESULTS: Analysis of the genotyping data revealed high levels of genetic polymorphism and an underlying North-south geographic pattern of genetic diversity that was highlighted by both the first dimension of the multi-dimensional scaling plot and the Neighbour network reconstruction. We observed a moderate and weak population structure in Northern and Central-Southern breeds, respectively, with pairwise FST values between breeds ranging from 0.013 to 0.164 and 7.49 % of the total variance assigned to the between-breed level. Only 2.11 % of the variance explained the clustering of breeds into geographical groups (Northern, Central and Southern Italy and Islands). CONCLUSIONS: Our results indicate that the present-day genetic diversity of Italian goat populations was shaped by the combined effects of drift, presence or lack of gene flow and, to some extent, by the consequences of traditional management systems and recent demographic history. Our findings may constitute the starting point for the development of marker-assisted approaches, to better address future breeding and management policies in a species that is particularly relevant for the medium- and long-term sustainability of marginal regions.

Low levels of taurine introgression in the current Brazilian Nelore and Gir indicine cattle populations.

BACKGROUND: Nelore and Gir are the two most important indicine cattle breeds for production of beef and milk in Brazil. Historical records state that these breeds were introduced in Brazil from the Indian subcontinent, crossed to local taurine cattle in order to quickly increase the population size, and then backcrossed to the original breeds to recover indicine adaptive and productive traits. Previous investigations based on sparse DNA markers detected taurine admixture in these breeds. High-density genome-wide analyses can provide high-resolution information on the genetic composition of current Nelore and Gir populations, estimate more precisely the levels and nature of taurine introgression, and shed light on their history and the strategies that were used to expand these breeds. RESULTS: We used the high-density Illumina BovineHD BeadChip with more than 777 K single nucleotide polymorphisms (SNPs) that were reduced to 697 115 after quality control filtering to investigate the structure of Nelore and Gir populations and seven other worldwide populations for comparison. Multidimensional scaling and model-based ancestry estimation clearly separated the indicine, European taurine and African taurine ancestries. The average level of taurine introgression in the autosomal genome of Nelore and Gir breeds was less than 1% but was 9% for the Brahman breed. Analyses based on the mitochondrial SNPs present in the Illumina BovineHD BeadChip did not clearly differentiate taurine and indicine haplotype groupings. CONCLUSIONS: The low level of taurine ancestry observed for both Nelore and Gir breeds confirms the historical records of crossbreeding and supports a strong directional selection against taurine haplotypes via backcrossing. Random sampling in production herds across the country and subsequent genotyping would be useful for a more complete view of the admixture levels in the commercial Nelore and Gir populations.

Searching new signals for production traits through gene-based association analysis in three Italian cattle breeds.

Genome-wide association studies (GWAS) have been widely applied to disentangle the genetic basis of complex traits. In cattle breeds, classical GWAS approaches with medium-density marker panels are far from conclusive, especially for complex traits. This is due to the intrinsic limitations of GWAS and the assumptions that are made to step from the association signals to the functional variations. Here, we applied a gene-based strategy to prioritize genotype-phenotype associations found for milk production and quality traits with classical approaches in three Italian dairy cattle breeds with different sample sizes (Italian Brown n = 745; Italian Holstein n = 2058; Italian Simmental n = 477). Although classical regression on single markers revealed only a single genome-wide significant genotype-phenotype association, for Italian Holstein, the gene-based approach identified specific genes in each breed that are associated with milk physiology and mammary gland development. As no standard method has yet been established to step from variation to functional units (i.e., genes), the strategy proposed here may contribute to revealing new genes that play significant roles in complex traits, such as those investigated here, amplifying low association signals using a gene-centric approach.

Comparison of colostrum and milk extracellular vesicles small RNA cargo in water buffalo.

Recently, much interest has been raised for the characterization of signaling molecules carried by extracellular vesicles (EVs), which are particularly enriched in milk (mEVs). Such interest is linked to the capability of EVs to cross biological barriers, resist acidification in the gastric environment, and exert modulation of the immune system, mainly through their microRNA (miRNA) content. We characterized the small-RNA cargo of colostrum EVs (colosEVs) and mEVs from Italian Mediterranean buffalo through next generation sequencing. Colostrum (first milking after birth) and milk (day 50 of lactation) were sampled from seven subjects from five farms. ColosEVs and mEVs were subjected to morphological characterization, followed by high-depth sequencing of small RNA libraries produced from total RNA. The main difference was the amount of EV in the two samples, with colostrum showing 10 to 100-fold higher content than milk. For both matrices, miRNA was the most abundant RNA species (95% for colosEVs and 96% for mEVs) and three lists were identified: colosEV-specific, mEV-specific and shared most expressed. Gene ontology (GO) enrichment analysis on miRNA targets highlighted many terms related to the epigenetic, transcriptional and translational regulations across the three lists, with a higher number of enriched terms for colosEV-specific miRNAs. Terms specific to colosEVs were related to "cell differentiation" and "microvillus assembly", while for mEV "cardiac and blood vessel development" and "mitochondria" emergerd. Immune modulation terms were found for both sample-specific miRNAs. Overall, both matrices carry a similar molecular message in terms of biological processes potentially modulated into receiving cells, but there is significant difference in the abundance, with colostrum containing much more EVs than milk. Moreover, colosEVs carry molecules involved in signal transduction, cell cycle and immune response, as for mEVs and EVs of other previously characterized species, but with a special enrichment for miRNAs with epigenetic regulation capacities. These beneficial characteristics of colosEVs and mEVs are essential for the calf and could also be exploited for the therapeutic purposes in humans, although further studies are necessary to measure the sanitization treatment impact on EV conservation, especially in buffalo where milk is consumed almost exclusively after processing.

High clonality of Mycobacterium avium subsp. paratuberculosis field isolates from red deer revealed by two different methodological approaches of comparative genomic analysis.

Mycobacterium avium subsp. paratuberculosis (MAP) is the aetiological agent of paratuberculosis (Johne's disease) in both domestic and wild ruminants. In the present study, using a whole-genome sequence (WGS) approach, we investigated the genetic diversity of 15 Mycobacterium avium field strains isolated in the last 10 years from red deer inhabiting the Stelvio National Park and affected by paratuberculosis. Combining de novo assembly and a reference-based method, followed by a pangenome analysis, we highlight a very close relationship among 13 MAP field isolates, suggesting that a single infecting event occurred in this population. Moreover, two isolates have been classified as Mycobacterium avium subsp. hominissuis, distinct from the other MAPs under comparison but close to each other. This is the first time that this subspecies has been found in Italy in samples without evident epidemiological correlations, having been isolated in two different locations of the Stelvio National Park and in different years. Our study highlights the importance of a multidisciplinary approach incorporating molecular epidemiology and ecology into traditional infectious disease knowledge in order to investigate the nature of infectious disease in wildlife populations.

Mitochondrial DNA control-region and coding-region data highlight geographically structured diversity and post-domestication population dynamics in worldwide donkeys.

Donkeys (Equus asinus) have been used extensively in agriculture and transportations since their domestication, ca. 5000-7000 years ago, but the increased mechanization of the last century has largely spoiled their role as burden animals, particularly in developed countries. Consequently, donkey breeds and population sizes have been declining for decades, and the diversity contributed by autochthonous gene pools has been eroded. Here, we examined coding-region data extracted from 164 complete mitogenomes and 1392 donkey mitochondrial DNA (mtDNA) control-region sequences to (i) assess worldwide diversity, (ii) evaluate geographical patterns of variation, and (iii) provide a new nomenclature of mtDNA haplogroups. The topology of the Maximum Parsimony tree confirmed the two previously identified major clades, i.e. Clades 1 and 2, but also highlighted the occurrence of a deep-diverging lineage within Clade 2 that left a marginal trace in modern donkeys. Thanks to the identification of stable and highly diagnostic coding-region mutational motifs, the two lineages were renamed as haplogroup A and haplogroup B, respectively, to harmonize clade nomenclature with the standard currently adopted for other livestock species. Control-region diversity and population expansion metrics varied considerably between geographical areas but confirmed North-eastern Africa as the likely domestication center. The patterns of geographical distribution of variation analyzed through phylogenetic networks and AMOVA confirmed the co-occurrence of both haplogroups in all sampled populations, while differences at the regional level point to the joint effects of demography, past human migrations and trade following the spread of donkeys out of the domestication center. Despite the strong decline that donkey populations have undergone for decades in many areas of the world, the sizeable mtDNA variability we scored, and the possible identification of a new early radiating lineage further stress the need for an extensive and large-scale characterization of donkey nuclear genome diversity to identify hotspots of variation and aid the conservation of local breeds worldwide.

Human CD34+ cells engineered to express membrane-bound tumor necrosis factor-related apoptosis-inducing ligand target both tumor cells and tumor vasculature.

Adenovirus-transduced CD34+ cells expressing membrane-bound tumor necrosis factor-related apoptosis-inducing ligand (CD34-TRAIL+ cells) exert potent antitumor activity. To further investigate the mechanism(s) of action of CD34-TRAIL+ cells, we analyzed their homing properties as well as antitumor and antivascular effects using a subcutaneous myeloma model in immunodeficient mice. After intravenous injection, transduced cells homed in the tumor peaking at 48 hours when 188 plus or minus 25 CD45+ cells per 10(5) tumor cells were detected. Inhibition experiments showed that tumor homing of CD34-TRAIL+ cells was largely mediated by vascular cell adhesion molecule-1 and stromal cell-derived factor-1. Both CD34-TRAIL+ cells and soluble (s)TRAIL significantly reduced tumor volume by 40% and 29%, respectively. Computer-aided analysis of TdT-mediated dUTP nick end-labeling-stained tumor sections demonstrated significantly greater effectiveness for CD34-TRAIL+ cells in increasing tumor cell apoptosis and necrosis over sTRAIL. Proteome array analysis indicated that CD34-TRAIL+ cells and sTRAIL activate similar apoptotic machinery. In vivo staining of tumor vasculature with sulfosuccinimidyl-6-(biotinamido) hexanoate-biotin revealed that CD34-TRAIL+ cells but not sTRAIL significantly damaged tumor vasculature, as shown by TdT-mediated dUTP nick end-labeling+ endothelial cells, appearance of hemorrhagic areas, and marked reduction of endothelial area. These results demonstrate that tumor homing of CD34-TRAIL+ cells induces early vascular disruption, resulting in hemorrhagic necrosis and tumor destruction.

Machine Learning Data Analysis Highlights the Role of Parasutterella and Alloprevotella in Autism Spectrum Disorders.

In recent years, the involvement of the gut microbiota in disease and health has been investigated by sequencing the 16S gene from fecal samples. Dysbiotic gut microbiota was also observed in Autism Spectrum Disorder (ASD), a neurodevelopmental disorder characterized by gastrointestinal symptoms. However, despite the relevant number of studies, it is still difficult to identify a typical dysbiotic profile in ASD patients. The discrepancies among these studies are due to technical factors (i.e., experimental procedures) and external parameters (i.e., dietary habits). In this paper, we collected 959 samples from eight available projects (540 ASD and 419 Healthy Controls, HC) and reduced the observed bias among studies. Then, we applied a Machine Learning (ML) approach to create a predictor able to discriminate between ASD and HC. We tested and optimized three algorithms: Random Forest, Support Vector Machine and Gradient Boosting Machine. All three algorithms confirmed the importance of five different genera, including Parasutterella and Alloprevotella. Furthermore, our results show that ML algorithms could identify common taxonomic features by comparing datasets obtained from countries characterized by latent confounding variables.