The rumen is a unique natural habitat, exhibiting an unparalleled genetic resource of fibrolytic enzymes of microbial origin that degrade plant polysaccharides. The objectives of this study were to identify the principal plant cell wall-degrading enzymes and the taxonomic profile of rumen microbial communities that are associated with it. The cattle rumen microflora and the carbohydrate-active enzymes were functionally classified through a whole metagenomic sequencing approach. Analysis of the assembled sequences by the Carbohydrate-active enzyme analysis Toolkit identified the candidate genes encoding fibrolytic enzymes belonging to different classes of glycoside hydrolases(11,010 contigs), glycosyltransferases (6366 contigs), carbohydrate esterases (4945 contigs), carbohydrate-binding modules (1975 contigs), polysaccharide lyases (480 contigs), and auxiliary activities (115 contigs). Phylogenetic analysis of CAZyme encoding contigs revealed that a significant proportion of CAZymes were contributed by bacteria belonging to genera Prevotella, Bacteroides, Fibrobacter, Clostridium, and Ruminococcus. The results indicated that the cattle rumen microbiome and the CAZymes are highly complex, structurally similar but compositionally distinct from other ruminants. The unique characteristics of rumen microbiota and the enzymes produced by resident microbes provide opportunities to improve the feed conversion efficiency in ruminants and serve as a reservoir of industrially important enzymes for cellulosic biofuel production.Electronic supplementary materialThe online version of this article (doi:10.1186/s13568-016-0310-0) contains supplementary material, which is available to authorized users.
Aim
Severe mental illnesses (SMI), such as bipolar disorder and schizophrenia, are highly heritable, and have a complex pattern of inheritance. Genome‐wide association studies detect a part of the heritability, which can be attributed to common genetic variation. Examination of rare variants with next‐generation sequencing may add to the understanding of the genetic architecture of SMI.
Methods
We analyzed 32 ill subjects from eight multiplex families and 33 healthy individuals using whole‐exome sequencing. Prioritized variants were selected by a three‐step filtering process, which included: deleteriousness by five in silico algorithms; sharing within families by affected individuals; rarity in South Asian sample estimated using the Exome Aggregation Consortium data; and complete absence of these variants in control individuals from the same gene pool.
Results
We identified 42 rare, non‐synonymous deleterious variants (~5 per pedigree) in this study. None of the variants were shared across families, indicating a ‘private’ mutational profile. Twenty (47.6%) of the variant harboring genes were previously reported to contribute to the risk of diverse neuropsychiatric syndromes, nine (21.4%) of which were of Mendelian inheritance. These included genes carrying novel deleterious variants, such as the GRM1 gene implicated in spinocerebellar ataxia 44 and the NIPBL gene implicated in Cornelia de Lange syndrome.
Conclusion
Next‐generation sequencing approaches in family‐based studies are useful to identify novel and rare variants in genes for complex disorders like SMI. The findings of the study suggest a potential phenotypic burden of rare variants in Mendelian disease genes, indicating pleiotropic effects in the etiology of SMI.
Introduction: Severe Mental Illnesses (SMI), such as bipolar disorder and schizophrenia, are highly heritable, and have a complex pattern of inheritance. Genome wide association studies detect a part of the heritability, which can be attributed to common genetic variation.Examination of rare variants with Next Generation Sequencing (NGS) may add to the understanding of genetic architecture of SMIs.
Methods:We analyzed 32 ill subjects (with diagnosis of Bipolar Disorder, n=26; schizophrenia, n=4; schizoaffective disorder, n=1 schizophrenia like psychosis, n=1) from 8 multiplex families; and 33 healthy individuals by whole exome sequencing. Prioritized variants were selected by a 4-step filtering process, which included deleteriousness by 5 in silico algorithms; sharing within families, absence in the controls and rarity in South Asian sample of Exome Aggregation Consortium.
Results:We identified a total of 42 unique rare, non-synonymous deleterious variants in this study with an average of 5 variants per family. None of the variants were shared across families, indicating a 'private' mutational profile. Twenty (47.6%) of the variant harboring genes identified in this sample have been previously reported to contribute to the risk of neuropsychiatric syndromes. These include genes which are related to neurodevelopmental processes, or have been implicated in different monogenic syndromes with a severe neurodevelopmental phenotype.Conclusion: NGS approaches in family based studies are useful to identify novel and rare variants in genes for complex disorders like SMI. The study further validates the phenotypic burden of rare variants in Mendelian disease genes, indicating pleiotropic effects in the etiology of severe mental illnesses.Not a peer reviewed or publication accepted version 5
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