Operational taxonomic unit (OTU) occurrence
The indigenous Aseel breed presented the highest number of non-singleton non-doubleton (with > 2 members) OTUs (genetic distance based OTUs at 97% similarity curoff) (3461), followed by Ghagus (1911) and Nicobari (1767) (Table 1). The commercial broiler line presented the lowest number of OTUs (857). Observed OTU numbers were significantly (P < 0.05) higher in the indigenous breeds than that of the commercial broiler line (Fig. 1 and Additional file 1). Observed OTU numbers in the Aseel breed was higher than those of Ghagus and Nicobari. However, OTU numbers in Ghagus and Nicobari were comparable.
Based on Good’s cover- age index, 98.6, 99.1, 97.2 and 97.7% of gut microbial diversity were covered in Broiler, Aseel, Ghagus and Nicobari, respectively (Table 1).
Taxonomy Assignment
The assignment of consensus taxonomy resulted in the identification of 18 phyla, 138 genera and 296 phylotype-OTUs (Phylotype-OTUs were obtained after merging distance based OTUs with the same consensus taxonomy) being represented across the gut samples of the chicken population. Figure 1 provides an overview of the average CSS normalized relative abundance levels of most of the abundant microbiota at different taxonomic levels in the gut microbiota of different breeds/line. In Aseel the gut microbiota were dominated by Bacteroidetes (44.0%) followed by Firmicutes (43.0%), Proteobacteria (6.0%), Actinobacteria (1.0%) and Cyanobacteria (0.8%) that constituted 94.8% of the whole phyla. In the broiler line Firmicutes, Bacteroidetes, Cyanobacteria, Proteobacteria and Verrucomicrobia were the major phyla, which accounted for 81.0, 6.0, 6.0, 4.0 and 1.0% of total sequences, respectively. In Ghagus Bacteroidetes, Firmicutes, Proteobacteria, and Cyanobacteria were the major phyla, which accounted for 62.0, 26.0, 3.0 and 0.9% of total sequences, respectively. In Nicobari Bacteroidetes (53.0%), Firmicutes (24.0%), Proteobacteria (8.0%), Fusobacteria (5.0%), Verrucomicrobia(2.0%) and Cyanobacteria (2.0%) were predominant phyla. Overall, the two phyla Firmicutes and Bacteroides represented 77–88% of gut prokaryotes.
In the Broiler line, the Firmicutes phylum consists of predominant genera such as unidentified genus under family Lachnospiraceae (32.0%), Lactobacillus (18%), YS2 (6%), Ruminococcus (5%), Dorea (4%), unknown genus under order Clostridiales (4.0%), Oscillospira (3.0%), Coprococcus (2.0%), cc_115 group (2.0%), Clostridium (1%), and Blautia (15). Bacteroidetes phylum consists of predominant genus such as Bacteroides (5%). Proteobacteria phylum consists of predominant genera like an unidentified genus under order RF32 (2.0%), Escherecia (0.8%) and Bilophila (0.5%). The phylum Cyanobacteria is mainly represented by an unknown genus under order YS2, which constituted 6.0% of total sequences. The phylum Verrucomicrobia is proportionately less abundant and mainly represented by genus Akkermansia and an unidentified genus under family Cerasicoccaceae.
In Aseel, the Firmicutes phylum consists of predominant genera such as an unidentified genus under family Lachnospiraceae (11.0%), Oscillospira (6%), an unknown genus under order Clostridiales (3%), an unidentified genus under family Ruminococcacae (3.0%), Coprococcus (3.0%), Faecalibacterium (2.0%), Ruminococcus (2.0%), Dorea (2.0%), SMB53(2.0%), unidentified genus under family Christensenellaceae (2.0%) and Lactobacillus (1.0%). Bacteroidetes phylum consists of predominant genus such as an unidentified genus under order Bacteroidales (24.0%), Bacteroides (11.0%), an unknown genus under phylum Bacteroidetes (4.0%), an unknown genus under family S24-7 (2.0%), Paraprevotella (0.8%) and Prevotella (0.6%). Proteobacteria phylum consists of predominant genera like Anaerobiospirillum, Sutterella, Desulfovibrio, Escherecia representing 2.0,2.0,0.5 and 0.3% of sequences respectively. The Actinobacteria phylum is mainly represented by a genus Olsenella (1% of sequences).
In Ghagus, the Firmicutes phylum consists of predominant genera such as Faecalibacterium, SMB53, unknown genus under order Clostridiales, an unidentified genus under family Lachnospiraceae, Oscillospira, Megamonas, Ruminococcus, Lactobacillus and Claustridium representing 4.0,4.0,3.0,2.0,2.0,1.0,1.0, 1.0 and 0.5% of total sequences, respectively. Bacteroidetes phylum consists of predominant genus such as Bacteroides (25.0%), an unidentified genus under order Bacteroidales (22.0%), an unidentified genus under family S24-7 (5.0%), an unknown genus under phylum Bacteroidetes (2.0%), Prevotella (2.0%) and Odoribacter (0.9%). Proteobacteria phylum consists of predominant genera like Sutterella and Desulfovibrio, representing 2.0 and 0.8% of sequences respectively.
In Nicobari, the Firmicutes phylum consists of predominant genera such as an unidentified genus under family Lachnospiraceae, an unknown genus under order Clostridiales, Megamonas, Faecalibacterium, Lactobacillus, SMB53,Oscillospira, Coprococcus, Ruminococcus and Clostridium representing 4.0,3.0,3.0,3.0, 2.0,1.0,1.0, 0.9, 0.9 and 0.5%, respectively. Bacteroidetes phylum consists of predominant genera such as Bacteroides, an unidentified genus under order Bacteroidales, an unidentified genus under phylum Bacteroidetes, an unidentified genus under family S24-7, Parabacteroides, Paraprevotella, Prevotella, Parabacteroides and Odoribacter representing 28.0, 16.0,2.0,1.0,0.9,0.9,0.8 and 0.9% of total sequences. Proteobacteria phylum consists of predominant genera like Sutterella and Desulfovibrio, representing 4.0 and 1.0% of sequences, respectively.
A venn diagram depicting extent of overlap of phylotype-OTUs between different hosts has been presented in Additional file 1. Aseel, Broiler, Ghagus and Nicobari had 263,172,249 and 230 phylotype-OTUs, respectively. Only 27 phylotype-OTUs were specific to any breed or line (Aseel: 25; Broiler: 1; Ghagus: 8; Nicobari: 3), whereas, 35, 89 and 135 phylotype-OTUs were shared between 2, 3 and 4 groups, respectively.
Microbial alpha diversity and data rarefaction
Different alpha diversity metrices (the diversity within each breed or line) were estimated to assess different aspects of the community structure and the results are presented in Fig. 2 and Additional file 2. The mean observed richness (number of observed OTUs) was highest in the Aseel group followed by Ghagus and Nicobari and lowest in the broiler line. The species richness (or the number of species or OTUs) indices like ACE and Chao1 were higher (P < 0.01) in the indigenous breeds than that of the commercial broiler line. Among indigenous breeds Aseel had significantly higher ACE and Chao1 estimates than those of Ghagus or Nicobari.
The diversity (which takes into account both richness and evenness) estimators like Simpson, Shannon and Fisher were also higher (P < 0.01) in the indigenous breeds (Aseel, Ghagus and Nicobari) as compared to the commercial broiler line and these estimators were comparable among the indigenous breeds. Besides these estimators, rarefaction curves based on the Chao1 index were also plotted. The rarefaction curve depicts the correlation between the number of sequences and the number of OTUs and steeper the slope, the higher the diversity [21]. Rarefaction curve also indicated that the broiler line had lower diversity than those of the indigenous breeds (Additional file 3). Rarefaction curve approached asymptotic level for each breed or line, suggesting the availability of sufficient reads to rep- resent each microbiome community.
Microbial beta diversity
The beta diversity (the partitioning of biological diversity among breeds or along a gradient, e.g., the number of species shared between two breeds or lines) analysis was undertaken to assess the relationship of microbial communities of different breeds/line using different metrices to calculate the dissimilarity/distance matrix, like Bray-Curtis, Jensen-Shannon, unweighted UniFrac and weighted UniFrac.
The correlation between the distance matrix and metadata categories was tested using PERMANOVA, which reports an R2 value indicating the proportion of variation explained by this category, and a P value representing the statistical significance [22]. Homogeneity of group dispersions were also tested using PERMDISP. Beta diversity was visualized using nMDS as well as PCoA but due to space limitation only plots obtained using nMDS are presented. Results of beta diversity analysis including results of ordination using nMDS or PCOA are presented in Additional file 4.
PERMANOVA tests performed using all beta diversity metrices used in this study showed significant (P < 0.001) difference in community structure between different breeds/line both at OTU level and at Phylum level (Additional file 4). At OTU level, Jensen Shannon based PERMANOVA analysis had highest Pseudo–F (11.56) and R2 (0.553) values among all four distance metrices indicating that 55.3% of microbiota variation is explained by this category (breed) besides a significant p-value (P < 0.001). The weighted UniFrac based analysis at OTU level showed that breed explained 47.3% (R2) of microbial variation (PERMANOVA, pseudo–F 8.4, P < 0.001). At phylum level, Jensen Shannon based PERMANOVA analysis had highest Pseudo- F (18.54; P < 0.001) and R2 (0.665) value among all four distance metrices indicating that 66.5% of microbiota variation is explained by this category (breed) besides a significant p-value (P < 0.001). The weighted UniFrac based analysis at phylum level showed that breed explained 52.7% (R2) of microbial variation (PERMANOVA, pseudo–F 10.4, P < 0.001). The beta dispersion values (PERMDISP) were non-significant for all groups in all diversity metrices analysed at OTU or phylum level except in case of unweighted unifrac analysis for phylum data indicating homogeneous dispersion among groups.
Beta diversity plots visualized using ordination methods nMDS at OTU and phylum level using nMDS method of ordination have been presented in Fig. 3 and Additional file 5, respectively. Jaccard index resulted in similar plots in NMDS scaling as that of Bray Curtis distance both at OTU as well as at Phylum Level and hence, plots for Jaccard index have not been presented.
The NMDS scaling based on all five distance metrices showed clear visual separation of breeds/line at OTU level. When Jensen-Shannon or weighted uniFrac distance was used there was high degree of overlap between the indigenous breeds while only minor overlap between broiler and the indigenous breeds was evident at OTU level. When distance metrices like Bray-Curtis or unweighted UniFrac or Jaccard were used for NMDS plotting there was no overlap between the broiler Line and indigenous breeds at OTU level but there were high degree of overlaps among indigenous breeds. At phylum level, there was high degree of overlap between the indigenous breeds but only minor overlap between Broiler and indigenous breeds (Aseel or Nicobari or Ghagus) was observed and extent of overlap between breeds/line varied with the distance metric used. In case of weighted UniFrac distance there was considerable overlap between broiler and Aseel, minor overlap between broiler and Nicobari and no overlap between broiler and Ghagus. While in case of unweighted UniFrac minor overlap between broiler and Nicobari was observed with no overlap between Ghagus and broiler or between Aseel and broiler. In case of Bray –Curtis distance/Jaccard index minor overlap was observed between broiler and Ghagus and no overlap between broiler and Nicobari or between broiler and Aseel. When Jensen –Shannon divergence was used there was minor overlap between broiler and Aseel and no overlap between broiler and Ghagus or broiler and Nicobari. Overall, it is noticeable that even at Phylum level there was very low level of overlap between indigenous breeds and the broiler line indicating almost completely different microbial community compositional distribution pattern between these two categories.
Differential abundances at different taxonomic levels
The 157 phylotype-OTUs (with ≥ 4 members and prevalence in > 20% samples) were taxonomically placed (using RDP classifier and Greengene database) into a total of 91 genera with 88, 69, 88 and 87 genera in Aseel, broiler, Ghagus and Nicobari, respectively. At family level sequences were classified into a total of 68 families with 66, 54, 65 and 68 families in Aseel, broiler, Ghagus and Nicobari, respectively. At order level sequences were classified into a total of 44 orders with 42, 32, 42 and 44 orders in Aseel, broiler, Ghagus and Nicobari, respectively. At class level sequences were classified into a total of 35 classes with 34, 29, 35 and 35 classes in Aseel, broiler, Ghagus and Nicobari, respectively. At phylum level sequences were classified into a total of 20 phyla with 19, 18, 20 and 20 phyla in Aseel, broiler, Ghagus and Nicobari, respectively.
Out of 157 Phylotype-OTUs, edgeR analysis with FDR correction indicated that 88 phylotype-OTUs were significantly different in abundance between breeds/line. Major Phylotype-OTUs (top 41 out of 88 phylotype-OTUs in term of CSS normalized abundance) with significant difference in abundances between breeds/line along with taxonomy (last classified level) has been presented in Fig. 4. Many phylotype-OTUs containing large number of sequences had low taxonomic resolution (having a taxonomic resolution only down to the order level). Comparisons between group pairs using Mann-Whitney U test indicated that among the 41 most abundant phylotype-OTUs there were significant difference in abundance of 24, 19, 21, 24, 26 and 6 phylotype-OTUs between Aseel vs broiler, Aseel vs Ghagus, Aseel vs Nicobari, broiler vs Ghagus, respectively. Interestingly, abundance of many phylotype-OTUs such as OTU1000062 (order Bacteroidales), OTU100296(family equivalent S24-7 uncultured gut microbial group), OTU102407 (genus Bacteroides), OTU1057116 (phylum Bacteroidetes), OTU168571 (species Bacteroides barnesiae), OTU1758401(genus equivalent SMB53 uncultured gut group) and OTU4324240 (genus Faecalibacterium) and were very low in the broiler line although these were highly abundant in all indigenous breeds. On the other hand abundance of OTU137026 (genus Lacobacillus), OTU1021172 (species Lactobacillus salivarius), OTU137026 (species Lactobacillus agilis), OTU181074 (genus equivalent CC115 gut group) and OTU549991 (species Lactobacillus helveticus) were higher in the broiler line than those of indigenous breeds.
Many phylotype OTUs were significantly higher in abundance in Aseel than in Ghagus or Nicobari. The notable ones, besides others, include OTU1000113(order Burkholderiales), OTU100567 (genus Ruminococcus), OTU839684 (family Lachnospiraceae), OTU586453(family Christensenellaceae), OTU1010876(genus Oscillospira), OTU1057116(phylum Bacteroidetes) OTU 167741 (genus Dorea) and OTU1649772 (species Escherichia coli). On the other hand abundance of OTU1021172 (species Lactobacillus salivarius) and OTU1066621 (genus Prevotella) were higher in Ghagus than in Aseel. Abundance of few phylotype OTUs such as OTU100296 (family S24-7) and OTU1758401 (family SMB53) were lower in Nicobari than in Aseel or Ghagus. Abundance of OTU4369050 (family Fusobacteriaceae) was higher in Nicobari than in Aseel or Ghagus. Abundance of OTU1066621(genus Prevotella) was significantly higher in Ghagus than in Aseel or Nicobari.
Out of 91 genera having mean abundance of ≥ 4 and prevalence of > 20%, twenty four genera were significantly different in relative abundance between breeds/line. Genera having significant differences in abundance between breeds/line have been presented in Additional file 6. Sequences not assigned to any genera remained major part of total sequences in all groups. Mann-Whitney U test indicated that there were significant difference in abundance of 34, 12, 12, 28, 31 and 4 genera between Aseel vs broiler, Aseel vs Ghagus, Aseel vs Nicobari, broiler vs Ghagus, broiler vs Nicobari and Ghagus vs Nicobari groups, respectively. The broiler line had significantly higher abundance of unclassified Bilophila, unclassified Blautia, unclassified cc_115, Defluvitella, Escherichia, Lactobacillus and unclassified Lactobacillus as compared to indigenous breeds. Indigenous breeds had significantly higher abundance of unclassified Bacteroides, Barnesiella, Faecalibacterium, Helicobacter, unclassified Odoribacter and unclassified Parabacteroides as compared to the broiler line. Some of the genera like Anaerorhabdus, Collinsella, Eubacterium, Marvinbryantia, unclassified Methanobrevibactor, unclassified Olsenella, p75_a5, unclassified Paraprevotella, Succinatimonas and Vestibaculum were not detected in broiler but were detected consistently, although in low numbers, in indigenous breeds. The genus Blautia was detected in all broiler samples and only in two samples of Aseel. The genus Eggerthella was only detected in the broiler line. The genus Anaerobiospirillum was detected in considerable numbers in Aseel and Nicobari but in only one sample of Ghagus. The genus Roseburia was detected only in Aseel and broiler but not in Ghagus or Nicobari.
Out of 72 families having mean abundance of ≥ 4 and prevalence of > 20%, metagenomeSeq analysis with FDR correction indicated that twenty eight families were significantly different in relative abundance between breeds/line. Families having significant difference in abundance between breeds/line have been presented in Additional file 7. Comparisons between different pairs of groups using Mann-Whitney U test indicated significant difference in abundance of 21, 10, 12, 20, 23 and 5 families between Aseel vs broiler, Aseel vs Ghagus, Aseel vs Nicobari, broiler vs Ghagus, broiler vs Nicobari and Gahgus vs Nicobari groups, respectively. The broiler line had significantly higher abundance of Lactobacillaceae as compared to indigenous breeds. Some of the prokaryaote families like unclassified Elusimicrobiaceae, Methanomassiliicoccaceae, Odoribacteriaceae, Oxalobacteraceae, Peptococcaceae, Peptostreptococcaceae, Porphyromonadaceae, Prevotellaceae, unclassified Rs_045, unclassified S24_7, unclassified Sphaerochaetaceae, unclassified Sphingobacteriaceae and Succinovibrionaceae were detected only in few samples in broiler but were detected more or less consistently although in low numbers in indigenous breeds. The family Ruminococcaceae as well as unclassified Ruminococcaceae was more abundant in Aseel and broiler followed by Ghagus. Large number of sequences remained unclassified upto family level. Abundance of Clostridiaceae was lowest in broiler followed by Nicobari.
Out of 45 orders meeting the minimum count and prevalence criteria, twenty two orders were significantly different in relative abundance between breeds/line. Orders having significant difference in abundance between breeds/line have been presented in Additional file 8. Comparisons between different pairs of groups using Mann-Whitney U test indicated significant difference in abundance of 18, 6, 12, 14, 17 and 1 orders between Aseel vs broiler, Aseel vs Ghagus, Aseel vs Nicobari, broiler vs Ghagus, broiler vs Nicobari and Gahgus vs Nicobari groups, respectively. The broiler line had significantly higher abundance of Enterobacteriales and Lactobacilales as compared to indigenous breeds. Indigenous breeds had significantly higher abundance of Bacteroidales and unclassified Bacteroidales as compared to the broiler line. Some of the orders like Anaeromonadales, Brachyspirales, CW040, Methanobacteriales, Sphaerochaetales, Spirochaetales and Turicbacterales were not detected in broiler but were detected consistently although in low numbers in indigenous breeds. The order Brachyspirales was only detected in Aseel and Nicobari. Abundance of Clostridiales was very high in Aseel and Broiler compared to Ghagus and Nicobari.
Class level abundance data of gut microbiota has been presented in Additional file 9. Out of 36 classes meeting the minimum count and prevalence criteria abundances of 30 classes were significantly different between groups. Comparisons between different pairs of groups using Mann-Whitney U test indicated significant difference in abundance of 24, 8, 14, 20, 20 and 9 classes between Aseel vs Broiler, Aseel vs Ghagus, Aseel vs Nicobari, Broiler vs Ghagus, Broiler vs Nicobari and Gahgus vs Nicobari groups, respectively. The broiler line had significantly higher abundance of Bacilli and Erysipelotrichi as compared to indigenous breeds. Indigenous breeds had significantly higher abundance of Bacteroidia as compared to the broiler line. Abundance of Clostridia was significantly higher in Aseel than Nicobari. Abundance of Clostridia was higher in broiler than those of Ghagus and Nicobari. Many classes were not detected consistently in broiler but were detected consistently although in low numbers in indigenous breeds.
Phylum level abundance data of gut microbiota has been presented in Additional file 10. Out of 19 Phyla edgeR analysis followed by FDR correction indicated that abundances of 5 phyla were significantly different between groups. Comparisons between different pairs of groups using Mann-Whitney U test indicated significant difference in abundance of 3, 0, 5, 3, 3 and 1 phyla between Aseel vs broiler, Aseel vs Ghagus, Aseel vs Nicobari, broiler vs Ghagus, broiler vs Nicobari and Gahgus vs Nicobari groups, respectively. The broiler line had significantly higher abundance of Fimicutes as compared to indigenous breeds. Indigenous breeds had significantly higher abundance of unclassified Bacteroidetes as compared to the broiler line. Some of the phyla like Deferribacteres, Elusimicrobia, Spirochaetes, TM7 and unclassified WPS2 were either not detected or detected in few samples in broiler but were detected consistently although in low numbers in indigenous breeds. At phylum level there was significantly higher abundance of Actinobacteria, unclassified Bacteriodetes, Firmicutes and TM7 in Aseel as compared to Nicobari. There was no difference in abundance of any phylum between Aseel and Ghagus. Abundance of phylum TM7 was significantly higher in Ghagus than in Nicobari.
The breed/Line specific biomarkers based on LEfSe algorithm
The LEfSe analysis identified biomarkers in the gut microbiota (specific taxa that varied in abundance consistently by chicken breed or line) that were indicative of gut microbiota of each breed or line. In total, 82, 35, 54, 37, 27, 21 and 14 biomarkers were identified with LDA scores > 2.0 at phylotype-OTU, species, genus, family, order, class and phylum levels, respectively. High abundance of genera Bacteroides, Oscillospira, Faecalibacterium, Coprococcus, Anaerobiospirillum, Sutterella, Olsenella, Paraprevotella, unclassified Clostridiacaea, Cloacibacillus, Turicibacter, Treponema, Collinsella, Succinatimonas, Gemmiger, Methanobrevibacter and Desulfovibrio were typical for Aseel breed (Fig. 5a). High abundance of genera or genus equivalent taxonomic groups Lactobacillus, Ruminococcus, unclassified Lactobacillaceae, Subdoligranulum, Dorea, cc_115, Blautia, Escherichia, Clostridium, Bilophila, Defluviitalea, Bifidobacterium and Eggerthella were typical for the broiler line. Similarly, higher abundance of few genera or genus equivalent taxonomic groups namely SMB53, Prevotella, Odoribacter, Parabacteroides, Akkermansia, YRC22 and RFN20 were typical to the Ghagus breed. Higher abundance of Fusobacterium, Meganomonas, Asteroleplasma, Barnesiella, Helicobacter, Elusimicrobia, WCHB1_41, Desulfovibrio, and Spirochaetes were typical to the Nicobari breed.
Cladogram of important biomarkers identified at different taxonomic levels in different breeds/line using LefSe with LDA scores > 3.5 has been presented in Fig. 5b. The class Coriobacteriia, orders such as unclassified Bacteroidetes and Aeromonadales, families like Christensenelaceae, Ruminococcaceae and Succinovibrionaceae were major biomarkers in the Aseel. The phylum Firmicutes, class Bacilli, order Enterobacteriales and families such as Lactobacillaceae and Enterobacteriacceae were top biomarkers in the broiler line. The phylum Bacteroidetes, classes TM7_3, Bacteroidia and Lentisphaeria, orders such as Bacteroidales and families like Odoribacteraceae, Paraprevotellaceae, Porphyromonadaceae, Prevotellaceae, S24_7, Clostridiaceae and Victivallaceae were top biomarkers in Ghagus. The phylum Elusimicrobia and Synergistetes, classes Fusobacteria, Elusimicrobia, Synergistia, Verruco_5, Epsilonproteobacteria, Betaproteobacteria and Pedosphaerae, orders such as Elusimicrobiales, Fusobacteriales, Burkholderiales and families such as Bacteroidaceae, Elusimicrobiaceae, Fusobacteriaceae, Alcaligenaceae and Synergistaceae were top biomarkers in Nicobari.
Correlation analysis
Family level correlations among microbes in Aseel, broiler, Ghagus and Nicobari are shown in Additional files 11, 12, 13 and 14, respectively. For Aseel, the occurrence of families which in- clude potentially pathogenic species such as Enterobacteriaceae, Clostridiaceae, Campylobacteraceae, Pasteurellaceae, Streptococcaceae, Staphylococcacae, Fusobacteriaceae, Enterococcaceae Corynebacteriaceae and Helicobacteraceae exhibited a positive correlation with each other, had a high positive correlation with Sutterellaceae, Oxalobacteraceae, Alcaligenaceae, Marinilabiacae, Victivallaceae, Deferribacteriaceae, Rhodospirillaceae, Methanocorpusculaceae, Flavobacteriaceae and Burkholderiaceae, and a high negative correlation with Christensenellaceae and Ruminococcacae and a low correlation with Lactobacillaceae and Bifidobacteriaceae. Families such as Lactobacillaceae, Peptococcaceae, Micrococcaceae, Actinomycetaceae, Bifidobacteriaceae, Lachnospiraceae, Coriobacteriaceae and Cytophagaceae exhibited a strong positive correlation with each other and a negative correlation with most other families. Surprisingly, Clostridiales family XIII Incertae sedis, Eubaccteriaceae, Methanobacteriaceae, Hyphomicrobiaceae and Moraxellaceae showed negative correlations with most of the families detected in Aseel (Additional file 11).
In case of the broiler line several small family level clusters with strong positive correlation with each other were detected. The families such as Sutarellaceae, Victivallaceae, Burkholderiaceae, Elusimicrobiaceae, Deferribacteriaceae, Rhodospirillaceae, Methanocorpusculacaea exhibited a strong positive correlation with each other. Campylobacteraceae, Fusobacteriaceae, Prevotellaceae, Rickenellaceae, Acidominococcaceae, Bacteroidaceae, and Desulfovibrionaceae exhibited a strong positive correlation with each other and negative correlation with most other families. Enterobacteriaceae, Pseudomonadaceae and Coriobacteriaceae showed a strong positive correlation with each other (Additional file 12).
In Ghagus several family level clusters of prokaryotes having strong positive correlations among themselves were detected such as :Suterellaceae, Victivallaceae, Burkholderiaceae, Elusimicrobiaceae, Deferribacteriaceae, Rhodospirillaceae, Methanocorpusculaceae, Sinobacteraceae, Erysipelotrichaceae and Alcaligenaceae; Lactobacillaceae, Desulfovibrionaceae and Enterobacteriaceae; Succinovibrionaceae, Helicobacteriaceae, Fusobacteriaceae, Bifidobacteriaceae and Peptostreptococcaceae, etc (Additional file 13).
In Nicobari also several family level clusters which exhibited a strong positive correlation with each other were detected such as: Peptococcaceae, Lachnospiraceae, Coriobacteriaceae, Desulfovibrionaceae, Bifidobacteriaceae, Acidaminococcaceae, Lactobacillaceae, Christensenellaceae, Oxalobacteraceae, Prevotellaceae, Mycoplasmataceae, Enterobacteriaceae, Ruminococcaceae, Hyphomicrobiaceae, Erysipelotrichiaceae and Clostridiaceae; Fusobacteriaceae, Enterococcaceae, Veillonellaceae and Bacillaceae but had a negative correlation with Enterobacteriaceae, Coriobacteriaceae, Erysipelotrichaceae, Lachnospiraceae, Hyphomicrobiaceae and Lactobacillaceae. The families such as Methanocorpusculaceae, Victivallaceae, Fusobacteriaceae, Campylobacteriaceae, Prevotellaceae, Veillonellaceae, Verrucomicrobiaceae and Bacteroidaceae exhibited a strong positive correlation with each other with a negative correlation with Coriobacteriaceae, Enterobacteriaceae, Erysipelotrichaceae, Lachnospiraceae, Leuconodtocaceae, Clostridiaceae, Hyphomicrobiaceae and Lactobacillaceae. Similarly, Enterobacteriaceae, Erysipelotrichaceae and Coriobacteriaceae had a strong positive correlation with each other. Lactobacillaceae, Hyphomicrobiaceae and Clostridiaceae had a strong positive correlation with each other (Additional file 14).