Most microbial species, including model eukaryote Saccharomyces cerevisiae, possess genetic capability to utilize many alternative nutrient sources. Yet, it remains an open question whether these ...manifest into assimilatory phenotypes. Despite possessing all necessary pathways, S. cerevisiae grows poorly or not at all when glycerol is the sole carbon source. Here we discover, through multiple evolved lineages, genetic determinants underlying glycerol catabolism and the associated fitness trade-offs. Most evolved lineages adapted through mutations in the HOG pathway, but showed hampered osmotolerance. In the other lineages, we find that only three mutations cause the improved phenotype. One of these contributes counter-intuitively by decoupling the TCA cycle from oxidative phosphorylation, and thereby hampers ethanol utilization. Transcriptomics, proteomics and metabolomics analysis of the re-engineered strains affirmed the causality of the three mutations at molecular level. Introduction of these mutations resulted in improved glycerol utilization also in industrial strains. Our findings not only have a direct relevance for improving glycerol-based bioprocesses, but also illustrate how a metabolic pathway can remain unexploited due to fitness trade-offs in other, ecologically important, traits.
•Mutations underlying efficient glycerol utilization by yeast identified.•Only three single nucleotide variants dramatically improve glycerol utilization.•Multi-omics analysis and metabolic modeling affirms causality of mutations.•Industrial yeasts with improved glycerol uptake constructed.•Operational decoupling of TCA cycle from oxidative phosphorylation observed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The recent advancements in forward genetics have expanded the applications of mutation techniques in advanced genetics and genomics, ahead of direct use in breeding programs. The advent of ...next-generation sequencing (NGS) has enabled easy identification and mapping of causal mutations within a short period and at relatively low cost. Identifying the genetic mutations and genes that underlie phenotypic changes is essential for understanding a wide variety of biological functions. To accelerate the mutation mapping for crop improvement, several high-throughput and novel NGS based forward genetic approaches have been developed and applied in various crops. These techniques are highly efficient in crop plants, as it is relatively easy to grow and screen thousands of individuals. These approaches have improved the resolution in quantitative trait loci (QTL) position/point mutations and assisted in determining the functional causative variations in genes. To be successful in the interpretation of NGS data, bioinformatics computational methods are critical elements in delivering accurate assembly, alignment, and variant detection. Numerous bioinformatics tools/pipelines have been developed for such analysis. This article intends to review the recent advances in NGS based forward genetic approaches to identify and map the causal mutations in the crop genomes. The article also highlights the available bioinformatics tools/pipelines for reducing the complexity of NGS data and delivering the concluding outcomes.
Molecular marker-assisted selection (MAS) provides an efficient tool for pig breeding. In this study, according to the literature, we selected eight effective or causal mutations from eight ...functional genes, including five causal mutations in PHKG1 (rs330928088), MUC13 (rs319699771), IGF2 (g.3072G>A), VRTN (g.20311_20312ins291), and MYH3 (XM_013981330.2:g.-1805_-1810del) genes, and three effective mutations in LIPE (rs328830166), LEPR (rs45435518), and MC4R (rs81219178) genes, to investigate their potential breeding effect in 418 Lulai pigs. The linear model was used to analyse the association between mutations and intramuscular fat (IMF) content, average backfat thickness, and muscle moisture %. The results revealed that amongst the three effective mutations, only the mutation in the LEPR gene, which affects IMF deposition, was significantly associated with IMF content. However, the other molecular markers were not significantly associated with the affected traits reported in previous studies, and these mutations are ineffective for MAS in the Lulai black pig population. Therefore, causal mutations in PHKG1, IGF2, and VRTN genes, and an effective mutation in LEPR gene could be used as effective breeding makers for MAS in Lulai pigs. These results can provide helpful information for further breeding in Lulai black pigs. La sélection assistée par marqueur moléculaire (MAS — « molecular marker-assisted selection ») offre un outil efficace pour la reproduction des porcs. Dans cette étude, selon la littérature, nous avons choisi huit mutations efficaces et causales provenant de huit gènes fonctionnels, incluant cinq mutations causales dans les gènes PHKG1 (rs330928088), MUC13 (rs319699771), IGF2 (g.3072G>A), VRTN (g.20311_20312ins291) et MYH3 (XM_013981330.2:g.-1805_-1810del), et trois mutations efficaces dans les gènes LIPE (rs328830166), LEPR (rs45435518) et MC4R (rs81219178), afin d’étudier les effets potentiels de celles-ci sur la reproduction de 418 porcs Lulai. Le modèle linéaire a été utilisé pour analyser l’association entre les mutations et la teneur en gras intramusculaire (IMF — « intramuscular fat »), l’épaisseur moyenne du gras dorsal (ABT — « average backfat thickness »), et le pourcentage d’humidité dans le muscle (MMP — « muscle moisture percent »). Les résultats ont révélé que parmi les trois mutations efficaces, seule la mutation dans le gène LEPR, qui a un effet sur le dépôt d’IMF, était associée de façon significative à la teneur en IMF. Par contre, les autres marqueurs moléculaires n’étaient pas associés de façon significative avec les caractéristiques affectées rapportées dans les études préalables, et ces mutations sont non efficaces pour la MAS dans la population de porcs noirs Lulai. Donc, les mutations causales dans les gènes PHKG1, IGF2 et VRTN, et une mutation efficace dans le gène LEPR pourraient être utilisées comme marqueurs efficaces de reproduction pour la MAS chez les porcs Lulai. Ces résultats pourraient offrir de l’information utile pour la reproduction ultérieure chez les porcs noirs Lulai. Traduit par la Rédaction
Summary
There is an increasing interest in using whole‐genome sequence data in genomic selection breeding programmes. Prediction of breeding values is expected to be more accurate when whole‐genome ...sequence is used, because the causal mutations are assumed to be in the data. We performed genomic prediction for the number of eggs in white layers using imputed whole‐genome resequence data including ~4.6 million SNPs. The prediction accuracies based on sequence data were compared with the accuracies from the 60 K SNP panel. Predictions were based on genomic best linear unbiased prediction (GBLUP) as well as a Bayesian variable selection model (BayesC). Moreover, the prediction accuracy from using different types of variants (synonymous, non‐synonymous and non‐coding SNPs) was evaluated. Genomic prediction using the 60 K SNP panel resulted in a prediction accuracy of 0.74 when GBLUP was applied. With sequence data, there was a small increase (~1%) in prediction accuracy over the 60 K genotypes. With both 60 K SNP panel and sequence data, GBLUP slightly outperformed BayesC in predicting the breeding values. Selection of SNPs more likely to affect the phenotype (i.e. non‐synonymous SNPs) did not improve the accuracy of genomic prediction. The fact that sequence data were based on imputation from a small number of sequenced animals may have limited the potential to improve the prediction accuracy. A small reference population (n = 1004) and possible exclusion of many causal SNPs during quality control can be other possible reasons for limited benefit of sequence data. We expect, however, that the limited improvement is because the 60 K SNP panel was already sufficiently dense to accurately determine the relationships between animals in our data.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
To explore the underlying mechanisms whereby noncoding variants affect transcriptional regulation, we identified nucleotides capable of disrupting binding of transcription factors and deactivating ...enhancers if mutated (dubbed candidate killer mutations or KMs) in HepG2 enhancers. On average, approximately 11% of enhancer positions are prone to KMs. A comparable number of enhancer positions are capable of creating de novo binding sites via a single-nucleotide mutation (dubbed candidate restoration mutations or RSs). Both KM and RS positions are evolutionarily conserved and tend to form clusters within an enhancer. We observed that KMs have the most deleterious effect on enhancer activity. In contrast, RSs have a smaller effect in increasing enhancer activity. Additionally, the KMs are strongly associated with liver-related Genome Wide Association Study traits compared with other HepG2 enhancer regions. By applying our framework to lymphoblastoid cell lines, we found that KMs underlie differential binding of transcription factors and differential local chromatin accessibility. The gene expression quantitative trait loci associated with the tissue-specific genes are strongly enriched in KM positions. In summary, we conclude that the KMs have the greatest impact on the level of gene expression and are likely to be the causal variants of tissue-specific gene expression and disease predisposition.
We describe a scanning procedure for the detection of protein C gene mutations and polymorphisms. The method is based on a combination of polymerase chain reaction (PCR) and denaturant gradient gel ...electrophoresis (DGGE) of 13 amplified fragments that cover exon I and most of the protein C coding regions. Exons IV and V are studied by routine direct sequencing. To validate our experimental conditions, and to verify that we were able to detect any point mutation in the fragments studied by DGGE, we tested a series of selected DNAs in which mutations had already been identified by another method. In addition, we studied the protein C gene of patients with qualitative deficiencies of protein C. In both instances, we detected all the causal mutations. We also present data on the detection of the three frequent neutral Caucasian polymorphisms in the protein C gene and on five novel mutations identified using the strategy described. These results show that DGGE is an efficient tool for establishing the molecular basis of hereditary protein C deficiencies.
Some Research Directions Vidyasagar, Mathukumalli
Computational Cancer Biology,
11/2012
Book Chapter
In this final chapter, three different directions for future research are sketched. The first problem is that of harmonizing prior knowledge about gene interaction networks that is scattered ...throughout the literature with the output of the phixer algorithm. This is formulated as a problem in graph theory, and possible approaches are indicated. The second problem is to identify ‘genomic machines’, that is, sets of genes that are connected by edges that are all over-expressed, or all under-expressed, in a common context. This problem is formulated as one of computing (or at least approximating) the stationary distribution of a large Markov chain, where the states correspond to individual genes. The last problem is to separate causal mutations (drivers of cancer) from coincidental mutations (passengers in cancer). It is surmised that a seven-dimensional vector known as the developmental gene expression profile plays a role in discriminating between drivers and passengers. Preliminary evidence from colorectal cancer is examined, and it is suggested that further studies should be carried out using recently published comprehensive analysis of colorectal cancer.
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FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Chronic inflammation surrounding bile ducts contributes to the disease pathogenesis of most cholangiopathies. Poor efficacy of immunosuppression in these conditions suggests biliary-specific ...pathologic principles. Here we performed biliary niche specific functional interpretation of a causal mutation (CD100 K849T) of primary sclerosing cholangitis (PSC) to understand related pathogenic mechanisms.
Biopsy specimens of explanted livers and endoscopy-guided sampling were used to assess the CD100 expression by spatial transcriptomics, immune imaging, and high-dimensional flow cytometry. To model pathogenic cholangiocyte-immune cell interaction, splenocytes from mutation-specific mice were cocultured with cholangiocytes. Pathogenic pathways were pinpointed by RNA sequencing analysis of cocultured cells and cross-validated in patient materials.
CD100 is mainly expressed by immune cells in the liver and shows a unique pattern around PSC bile ducts with RNA-level colocalization but poor detection at the protein level. This appears to be due to CD100 cleavage as soluble CD100 is increased. Immunophenotyping suggests biliary-infiltrating T cells as the major source of soluble CD100, which is further supported by reduced surface CD100 on T cells and increased metalloproteinases in cholangiocytes after coculturing. Pathogenic T cells that adhered to cholangiocytes up-regulated genes in the T-helper 17 cell differentiation pathway, and the CD100 mutation boosted this process. Consistently, T-helper 17 cells dominate biliary-resident CD4 T cells in patients.
CD100 exerts its functional impact through cholangiocyte-immune cell cross talk and underscores an active, proinflammatory role of cholangiocytes that can be relevant to novel treatment approaches.
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A primary biliary cholangitis causal mutation contributes to the pathogenic interaction of immune cells with the cells lining the bile ducts that also have a specific inflammation-driving role.
•Seven SNPs were evidenced in ovine KISS1R/GPR54 gene among Iranian sheep breeds.•Three novel SNPs lying in the coding region of ovine KISS1R/GPR54 gene were associated with prolificacy of Mehraban ...sheep.•The SNP g.3431C > A (p.195Phe > Leu) could be considered as a causal mutation impairing sheep prolificacy.
Fertility traits have the greatest financial impact on sheep production. In this study we aimed to characterize polymorphisms of the KISS1 receptor gene (KISS1R), also known as the G-protein-coupled receptor 54 gene (GPR54) that is reported to be involved in the control of puberty and reproductive function. Genomic DNA were obtained from 156 ewes of pure Mehraban and Shal Iranian native sheep and their crossbreeds with Romanov. The exploration of polymorphisms of the KISS1R/GPR54 gene (GenBank No: HM135393.1) was performed by single-strand conformation polymorphism analysis (SSCP) and Sanger sequencing. Seven single-nucleotide polymorphisms (SNPs) including g.396 T > G, g.456 T > C, g.475C > A, g.571 A > C, g.3431C > A, g.4108 G > A and g.4123C > A, were observed in the four breeds. Among these SNPs the g.3431C > A in the exon 4 was the only amino acid altering variant (p.195 Phe > Leu). Subsequent statistical analysis revealed that the minor A allele at this position had a significant (P < 0.01) negative effect on litter size (LS) and birth weight (BW) and could be considered as a causal mutation impairing these traits. No significant (P> 0.05) allelic association with the studied traits was found at the position g.396 T > G, g.456 T > C, g.475C > A and g.571 A > C. In contrast, carrier ewes of the SSCP pattern F (homozygous reference; g.4108 G/G, g.4123 C/C) showed a significantly (P < 0.01) higher LS than ewes carrying the patterns G (heterozygous; g.4108 G/A, 4123 C/A) or E (homozygous variant; g.4108 A/A, g.4123 C/C). The results of the present study provide additional evidences on the potential role of the KISS1R/GPR54 gene in controlling reproductive traits and particularly prolificacy in sheep.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Accurately identifying DNA polymorphisms can bridge the gap between phenotypes and genotypes and is essential for molecular marker assisted genetic studies. Genome complexities, including large-scale ...structural variations, bring great challenges to bioinformatic analysis for obtaining high-confidence genomic variants, as sequence differences between non-allelic loci of two or more genomes can be misinterpreted as polymorphisms. It is important to correctly filter out artificial variants to avoid false genotyping or estimation of allele frequencies. Here, we present an efficient and effective framework, inGAP-family, to discover, filter, and visualize DNA polymorphisms and structural variants (SVs) from alignment of short reads. Applying this method to polymorphism detection on real datasets shows that elimination of artificial variants greatly facilitates the precise identification of meiotic recombination points as well as causal mutations in mutant genomes or quantitative trait loci. In addition, inGAP-family provides a user-friendly graphical interface for detecting polymorphisms and SVs, further evaluating predicted variants and identifying mutations related to genotypes. It is accessible at https://sourceforge.net/projects/ingap-family/.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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