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USA 97 , — Peeters, N. These findings point to the likely involvement of other genes and environmental factors. Similarly, a homoplasmic mutation in a mitochondrial genome-encoded ribosomal RNA , called RNR1, causes postlingual deafness deafness that occurs after three years of age, when a child has already learned to speak. The clinical symptoms of this disease are associated with the administration of a particular type of antibiotic Prezant et al.
Therefore, environmental factors also contribute to the phenotypes associated with this mitochondrial mutation. What are some clues that may suggest a mitochondrial link to disease?
Some clinical features include a maternal family history and the involvement of several different tissues. Furthermore, because mitochondria function as the powerhouses of our cells, mitochondrial mutations often lead to more pronounced phenotypes in tissues that have high energy demands, such as brain, retinal, skeletal muscle, and cardiac muscle tissues. A number of clinical syndromes are currently believed to be associated with mitochondrial disease. Possible examples include Pearson syndrome, Leigh syndrome, progressive external ophthalmoplegia, exercise-induced muscle pain , fatigue, and rhabdomyolysis.
As previously mentioned, mitochondrial DNA in humans is always inherited from a person's mother Figure 4. As a result, we share our mitochondrial DNA sequence with our mothers, brothers, sisters, maternal grandmothers, maternal aunts and uncles, and other maternal relatives.
Due to the high mutation rates associated with mitochondrial DNA, significant variability exists in mitochondrial DNA sequences among unrelated individuals. However, the mitochondrial DNA sequences of maternally related individuals, such as a grandmother and her grandson or granddaughter, are very similar and can be easily matched.
Mitochondrial DNA sequence data has proved extremely useful in human rights cases, as it is a great a tool for establishing the identity of individuals who have been separated from their families. This approach has been very successful for the following reasons Owens et al. One of the most prominent researchers to use mitochondrial DNA sequence data to tackle human rights issues is Dr.
A particularly interesting example of Dr. King's work occurred in Argentina. As a result of a military dictatorship that overthrew the existing Argentinean government in , thousands of citizens disappeared between and , including infants and children who were abducted along with their parents. In addition, some children were born to women who were pregnant at the time of their kidnappings.
After the military dictatorship was defeated, a new government commission predicted that at least 8, and possibly as many as 30, people had been kidnapped, including documented infants and children. In , the grandmothers of these orphans formed the Associacion de Abuelas de Plaza de Mayo in an effort to identify their missing grandchildren, many of whom were illegally adopted by military families.
In , King used mitochondrial DNA sequence data to reunite some of these Argentinean orphans with their grandmothers. King collected blood samples from orphaned children and from women who had lost their children and grandchildren. Using mitochondrial DNA sequence data, she then matched more than 60 orphans with their biological families. In fact, as recently as , a young Argentinean man named Guillermo was finally reunited with his grandmother and sister. Guillermo's parents were kidnapped by security forces in October ; Guillermo's mother, Patricia, was pregnant at the time of her kidnapping, and Guillermo was born one month later.
Guillermo provided a blood sample to King's group, and his mitochondrial DNA sequence was a perfect match to that of one woman out of 2, in the database: Rosa, the mother of Patricia. As an additional test, the researchers obtained a DNA sample from Mariana, the known daughter of Patricia, who was at a friend's house on the day her parents were kidnapped.
As shown by this example, mitochondrial DNA sequences can be used to establish family ties with maternal relatives, even when both of a person's parents are missing. Over the years, a probable role for mitochondria in both aging and cancer has emerged. As a byproduct of their role as powerhouses of our cells, mitochondria generate reactive oxygen species ROS. ROS production has been proposed to cause somatic mitochondrial mutations. This can lead to a cycle in which ROS generate mutations, which in turn lead to disregulation of respiration and accumulation of more mutations.
Indeed, ROS production contributes to tissue aging due to decreased metabolic function and energy production, increased cell death, and a decreased capacity to replicate the genome. In , a link between colorectal cancer and somatic mitochondrial mutations was established by Polyak and colleagues.
These researchers cultured colorectal cancer cells taken from the tumors of 10 colorectal cancer patients. They then compared the mitochondrial DNA sequences of the tumor cell lines to the mitochondrial DNA sequences of cells from neighboring normal colon tissue from the same patient.
This side-by-side comparison was used to identify somatic mutations that had occurred in the mitochondrial DNA of the tumor cells. The researchers found that seven cell lines had acquired somatic mutations in their mitochondrial DNA sequences.
Three of the cell lines had acquired a single mutation, and four had acquired between two and three mutations, for a total of twelve mutations. Eight of the mutations were in protein-encoding mitochondrial genes, and four of the mutations were in mitochondrial ribosomal RNA rRNA genes. To confirm that the mitochondrial mutations had occurred in the tumors themselves and not during the culturing of the cells, the researchers next isolated DNA from the original tumor tissue and sequenced the mitochondrial DNA directly.
Tumor tissue was only available for five out of the seven patients with mitochondrial mutations in their cultured cells.
In all five cases, however, the same mutations were present in the primary tumor as in the cultured tumor cells. Furthermore, the mitochondrial mutations were all homoplasmic in both the primary tumor and in the cultured cells. Based on these findings, Polyak and colleagues suggested that the somatic mitochondrial mutations might have provided a growth advantage to a single cell that subsequently proliferated more rapidly than the surrounding cells.
Furthermore, based on the homoplasmic nature of the mitochondrial DNA mutation, they suggested that the mutation might have provided a replicative advantage to the mutant mitochondrial genome. In the years that followed, a number of other studies also established associations between somatic mitochondrial mutations and various forms of cancer, including leukemias and solid tumors. However, a causative link between mitochondrial mutations and cancer has not yet been firmly established.
Clearly, the role of the mitochondrial genome must be considered with respect to human genetic disease. The heterogeneity of the mitochondrial genome presents many unmet challenges to researchers. However, emerging technologies are likely to aid the discovery of underlying genetic mechanisms linking these powerhouses to neurodegenerative disease, cancer, diabetes, and aging. The key findings on the expression of MP genes from the Main Cows dataset were validated using two independent datasets Validation Cow and Validation Sheep.
Both validation sets confirmed the general trends of MP gene expression and co-expression in tissues. Firstly, both validation datasets confirmed the over-expression of MP genes in heart and skeletal muscles, and under-expression in blood leukocytes as in the adult tissues of the Main Cows dataset Additional file 11 - We investigated the poor correlation of gene expression in thyroid between the Main Cows and the Validation Cow.
These genes were mainly enriched for metabolic pathways, pyruvate metabolism and synthesis of antibiotics. Scatterplot of log2 fold change values of differentially expressed mitochondrial protein genes from nuclear genome in the Main Cows against the Validation Cow. Finally, the overlap of genes in Nu MP- Mt MP clusters across the Main Cow and validation datasets was higher than would be expected if genes were randomly allocated to clusters.
Similarly, a considerable proportion of Nu MP genes and also non-mitochondrial protein genes, were in common across datasets Fig. Mitochondrial protein genes encoded by the nuclear genome Nu MP genes , b.
Mitochondrial protein genes encoded by the mitochondrial genome Mt MP genes and c. This study described and validated specific patterns of differential expression for over mitochondrial protein genes, encoded by the nuclear and mitochondrial genomes, in bovine across different tissues.
MP genes were over-expressed in tissues with high reported metabolic demand heart, skeletal muscles, tongue, and kidney cortex: Table 4 , and under-expressed in tissues with low reported energy demand adipose tissue and blood leukocytes: Table 4. Similarly, skeletal muscles, which has low resting energy demand, are capable of spiking by almost fold during short intensive exercise [ 42 , 43 ].
The observed higher expression of MP genes in the tongue seems likely because the tongue is a muscular organ. Furthermore, results from the heart and skeletal muscles group reinforced the importance of OXPHOS and metabolic pathways in energy metabolism in these tissues.
A high expression of MP genes specifically in kidney cortices may be attributed to energy generation taking place at the proximal and distal convoluted tubules, which are also the site for active reabsorption of metabolites [ 45 , 46 ].
Among the tissues with under-expression of MP genes, only adipose tissue in human has a published metabolic rate. In keeping with our observed low MP gene expression in adipose, the metabolic rate of human adipose tissues was low 3.
On the other hand, leukocytes and other tissues with under-expression for MP have mainly non-energy related mitochondrial functions, such as redox signalling and controlling apoptosis [ 47 ], which, in part, could explain the incidence of under-expression of MP genes in blood leukocytes.
Further, results from the analysis of group of tissues showing MP gene under-expression revealed a low number of DE genes in common across these tissues and no enrichment for energy pathways support a diminished role of mitochondrial energy function in leukocytes.
As for the adult cows, the highest expression of MP genes in the foetal heart tissue was expected considering the early foetal development and establishment of the heartbeat occurs as early as 3 weeks in the bovine foetus.
In contrast to adult cows, the low expression of MP genes in foetal leg muscle was likely attributable to only partial development and non-functionality of the muscle. Skeletal muscle development, mainly secondary myogenesis, is initiated in the foetal stage from 9 weeks post-fertilization to parturition [ 48 ] and our foetal calves were around 16 weeks old.
Generally, the remaining foetal tissues measured in this study are reported to be functionally inert in the foetal development stage, including lungs [ 49 ] and explains the under-expression of the MP genes. In general, the expression profiles of MP genes in a tissue were consistent as indicated by clustering of same tissue of two or more animals within the dataset.
Nonetheless, some tissues were exceptions, including foetal livers may be attributed to the sampling and cellular heterogeneity of the samples because each cell type may have a specific expression profile. To sum up, the expression of MP genes in this study concurs with the energy demand of tissues where known implying that the increased energy demand may be met through increased expression of MP genes.
Furthermore, previous studies report that there is a specific correlation between mRNA and protein quantity across tissues [ 50 , 51 ]. Besides, energy demand in tissues as the basis of increased transcription rates of MP genes, high Mt MP gene expression could also result from increased mitochondrial genome copy numbers. Mitochondrial DNA copy number differs considerably across tissue types, but remains closely regulated within a tissue type [ 23 ]. Studies in humans indicate that mitochondrial genome copy numbers are aligned with tissue energy demands: for example heart, skeletal muscle, omental fat, and blood leukocytes had , , — and 91 copies per diploid nuclear genome respectively [ 52 , 53 , 54 ].
Studies comparing copy number and gene expression of all Mt MP genes across tissues are scarce. A study in striated muscles cardiac, type 1 skeletal muscle and type 2 skeletal muscles of rabbit [ 55 ] demonstrated that the expression of Mt MP gene CYTB was proportional to mitochondrial copy number.
Thus, it is plausible that the varying gene expression indicating energy requirements of tissue types are modulated through their mitochondrial DNA copy number. The first phenomenon of occurrence of DE Mt MP genes in single direction has not been previously reported to the best of our knowledge.
A possible explanation of this phenomenon rests in the mechanism of transcription because the entire mitochondrial genome is transcribed as a near-complete polycistronic unit [ 56 , 57 ], so that almost all mitochondrial genes are transcribed as one unit.
The initiation of transcription, particularly at HSP2 promotor site on the mitochondrial genome generates a near-complete polycistronic unit [ 58 ]. The co-expression of mitochondrial protein genes was a prominent finding in the current study. Co-expression of MP gene in Mt MP- Nu MP cluster was further tested to be non-random and non-random co-expression of genes are previously reported across species [ 30 ].
Similarly, results from MP gene expression study in humans showed a significant correlation between Mt MP and Nu MP gene expression within tissues [ 60 ], suggesting close coordination between nuclear and mitochondrial genomes in relation to energy demand. The Nu MP cluster was enriched for metabolic pathways which is another important energy metabolism component of mitochondria. This indicated the potential role of TADs in co-expression of mitochondrial protein gene in our study.
As such, the intra-TAD gene co-expression was not different from random for most chromosomes in another study [ 61 ]. Overall, there were high correlation and consistency evident in the expression differential expression and co-expression of mitochondrial protein genes in tissue across the datasets. However, we have not considered for the physiological states, number of tissues sampled, and sequencing platforms employed in our validation study.
The activity of thyroid and thyroid hormone synthesis are reportedly increased during pregnancy in human [ 62 ] and thyroid hormones are known to regulate metabolism [ 63 ].
The interaction of thyroid and MP function in metabolism is an area of interest for further investigation but beyond the scope of current work. Secondly, we based the differential gene expression of a gene in tissue to the mean expression across all other tissues where both the number of tissues and tissue types were not completely identical across the datasets 29 tissues in Main Cows, 18 tissues in Validation Cow and 15 tissues in Validation Sheep.
Thereby, expression in tissue across the datasets has been compared to the mean expression of different sample sizes, which might vary across the datasets. Mitochondrial protein genes were differentially expressed across tissues. Tissues with high energy demand showed over-expression and under-expression was observed in tissues with low energy requirements, which suggests a link between mitochondrial protein gene expression and the energy demand of each tissue.
Furthermore, mitochondrial protein genes from both genomes Nu MP and Mt MP were significantly co-expressed and enriched for co-functionality. This implies that it is necessary to consider mitochondrial protein genes from both genomes in studies related to mitochondrial function.
Mitochondrial protein gene expression analysis may be extrapolated to production traits such as feed efficiency, heat tolerance, adaptability to cold climate, to further elucidate their role in relation to energy metabolism. The standard best practice recommendations for RNA-seq is at least three samples of each tissue from different individuals [ 64 ]. This study utilized RNAseq from three cows; two Holstein cows and their foetuses, and one Holstein cow from a previous study [ 27 ].
As the cows in the two datasets were physiologically different due pregnancy status and also used different sequencing platforms, we analysed them separately and the results from the two cows dataset Main Cows was validated in the one cow dataset Validation Cow.
Further, gene expression patterns in cattle were validated in a sheep dataset previously published [ 65 ], which is a closely related species Validation Sheep [ 37 ]. The Main Cows dataset had RNAseq from 29 tissues from two adult cows and six tissues from two 16 weeks old foetuses. The Validation Cow data consisted of RNAseq reads from 18 tissues, and the Validation Sheep data were gene expression counts for a subset of tissues 15 tissue types of three Texel x Blackface adult females.
The tissue-specific gene expression patterns in the Main Cows dataset were validated using the validation datasets. The ethical approval, including the permission to euthanise the animals of the Main Cows datasets were obtained from the Department of Jobs, Precincts and Regions Ethics Committee Application No.
Cow had a male foetus F , and cow had a female foetus F. Both foetuses were from the same sire half-sibs. Other tissues were sampled following euthanasia of the animals.
The cows were euthanised individually by a trained veterinarian and not within line of sight of another deceased animal to minimise stress. Once pronounced dead, all tissue types were dissected from the animal. Subcutaneous fat was sampled from the rib region.
For this study, we generated data for 35 samples 29 tissues from adult cows and six from the foetuses Table 5. One hundred and fifty bases paired-end reads were called with bcltofastq and output in fastq format. The quality of the libraries and alignment are as presented in Additional file 2.
Poor-quality bases were filtered, and sequence reads trimmed using an in-house script. Only paired reads were retained for alignment. For each library, paired-end reads were mapped to Ensembl bovine genome UMD3. Aligned reads were checked for quality using Qualimap 2 [ 68 ], and unique mapping reads for samples Additional file 3. The R package featureCounts [ 69 ] was used to generate a count matrix of read counts per gene for every sample.
Mitochondrial protein genes in the current study were based on the list of MP identified in humans, available in Mitocarta 2. Additionally, 24 non-protein coding genes from the mitochondrial genome 22 tRNA s and 2 rRNA s were also included in the analysis.
The mitochondrial protein gene expression profiles in tissues are expected to be similar across mammalian species because they share a very important mitochondrial function [ 72 , 73 ]. The lowly expressed genes were filtered out using function filterByExpr of edgeR package for differential expression analysis in R [ 74 ].
Differential expression of genes was analysed using the glmQLFit function. A model was fitted to the data with a design matrix of an overall mean of gene expression counts across all other tissues as the intercept and tissue as a fixed effect, i.
A list of DE genes, along with their fold changes, was generated and summarized for each tissue. A gene was considered as differentially expressed DE in tissue if its expression was significantly higher than the mean expression of same gene across all other tissues i. In addition, we looked at the number of DE MP genes by genome i.
The foetal tissues were analysed separately following the procedures implemented for the adult cows. The functionally associated genes tend to be co-expressed, and this is used to infer novel function as well as to identify candidate genes in diseases and their prediction [ 28 ]. We analysed the co-expression cluster involving MP genes for;. Briefly, we mapped the co-expressed bovine genes across the clusters to the putative bovine TADs derived from the IMR90hg18 [ 78 ] and genes mapped to TADs.
Of this, co-expressed genes were distributed in groups of 2 or more per TAD. We compared this to averages from random samples of genes from TAD mapping genes across all clusters The DAVID software was used to investigate the functional enrichment of differentially expressed genes within a tissue and co-expressed genes across tissues: up to genes maximum permissible in DAVID were selected and analysed for over-representation in KEGG Kyoto Encyclopedia of Genes and Genomes pathways [ 79 ].
The patterns of MP gene expression in tissues of Main Cows were validated using two previously published datasets: a lactating Holstein cow 2 years old, 65 days in milk with 18 tissues additional file 17 [ 27 ] i.
Validation Cow ; and three adult female Texel x Scottish Blackface sheep from the sheep gene expression atlas project [ 37 ], which were aged about 2 years and locally Scotland acquired i. Validation Sheep. Depending on the number of tissues in common with cattle datasets, 15 tissues were chosen from the sheep study Additional file The Validation Cow was analysed separately due to its difference in physiological status compared to the Main Cows dataset.
The RNAseq reads of the Validation Cow were processed, aligned, gene counts generated and analysed following the protocols for Main Cows. Similarly for sheep, the raw gene counts [ 65 ] were normalized and subjected to standard processing and analyses for differential expression and co-expression. In sheep, MP genes were identified as overlapping the Mitocarta 2.
The pattern of MP gene expression across tissues was visualized with a heatmap and co-expression networks as described for Main Cows. One of the purposes of validation was to look at the consistency of gene expression patterns across datasets.
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