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Does zygosity have meaning for mitochondrial variants?

Does zygosity have meaning for mitochondrial variants?


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I am working on a system that annotates variants in human DNA sequences. One of the pieces of information reported is the zygosity of the variant. I noticed that mitochondrial variants are also shown to be either homo- or heterozygous.

How does that make sense? Does it make sense? As far as I know, the mitochondrial DNA is just a single, circular DNA molecule. So I can understand considering all mitochondrial variants heterozygous, by definition. I could also accept that one could think of them as homozygous by definition. I just don't see how some variants can be homo- and others heterozygous. Am I missing something or is the annotation system I'm using not making sense?


You abosolutely can have mixed populations of mitochondria in a cell (it is in fact very common). Therefore when you sequence the mtDNA you will get a completely variable percentace of reads containing a variant from close to 0% to 100% (there is a lower limit based on the quality and read depth of the sequencing data).

You can't consider the variants to be heterozygous or homozygous as conventional zygosity doesnt apply. Heteroplasmic and homoplasmic are the terms which are used.


Targeting Alzheimer's disease neuronal mitochondria as a therapeutic approach

Isaac G. Onyango , Gorazd B. Stokin , in Clinical Bioenergetics , 2021

Editing mtDNA mutations

Acquired mtDNA mutations participate in the pathophysiology of AD [ 66 , 67 ], and somatic mtDNA mutations are increased in AD brains. The common mtDNA 5 kilobase (kb) deletion is elevated 15-fold in AD brains [ 68 , 69 ], and somatic mtDNA control region (CR) mutations are increased by 73% in AD brains [ 70 ]. Mitochondrial-targeted transcription activator-like effector nucleases (mitoTALENs) can correct mtDNA mutations in cultured human cells from patients with an mtDNA disease [ 71 , 72 ] and correct induced mtDNA mutation in vivo in mouse models [ 73 ]. Mitochondrially targeted zinc figure nucleases (mtZFNs) [ 74 ] are another tool for specific removal of mtDNA mutations with a relatively low risk for interaction with the cell's nuclear DNA and are able to remove a pathogenic mtDNA mutation in vivo mouse experiment [ 75 ]. Almost all adult cells are heteroplasmic for mtDNA due to age-related acquired mtDNA mutations. The degree of mutation load determines the onset of clinical symptoms, a phenomenon known as the threshold effect [ 76 ]. Clinical symptomatology can be alleviated by shifting the existing equilibrium between healthy and mutated mtDNA in different ways [ 77 ]. Unlike CRISPR and mitoTALENs technologies that correct mtDNA mutations, mtZFN techniques act by destroying mtDNA mutation-bearing mitochondria, leading to a repopulation of cells with healthy mitochondria. This strategy assumes that after selective destruction of the mutated mtDNA, healthy mtDNA will prevail [ 78 ]. This is appealing for human clinical applications because it avoids the use of gene-editing techniques, which might erroneously disrupt the function of normal genes of the treated cells [ 73–75 , 79 , 80 ].


ORIGINAL RESEARCH article

Zixian Wang 1,2,3,4† , Hui Chen 1,2,3† , Min Qin 1,2,3 , Chen Liu 5 , Qilin Ma 6 , Xiaoping Chen 7 , Ying Zhang 8 , Weihua Lai 2 , Xiaojuan Zhang 2* and Shilong Zhong 1,2,3,4*
  • 1 Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, School of Medicine, South China University of Technology, Guangzhou, China
  • 2 Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
  • 3 Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
  • 4 School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
  • 5 Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
  • 6 Department of Cardiology, Xiangya Hospital, Central South University, Changsha, China
  • 7 Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, China
  • 8 Department of Cardiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China

Plasma lipids have been at the center stage of the prediction and prevention strategies for cardiovascular diseases (CVDs), and novel lipidomic traits have been recognized as reliable biomarkers for CVD risk prediction. The mitochondria serve as energy supply sites for cells and can synthesize a variety of lipids autonomously. Therefore, investigating the relationships between mitochondrial single nucleotide polymorphism (SNPs) and plasma lipidomic traits is meaningful. Here, we enrolled a total of 1,409 Han Chinese patients with coronary artery disease from three centers and performed linear regression analyses on the SNPs of mitochondrial DNA (mtDNA) and lipidomic traits in two independent groups. Sex, age, aspartate aminotransferase, estimated glomerular filtration rate, antihypertensive drugs, hypertension, and diabetes were adjusted. We identified three associations, namely, D-loopm.16089T>C with TG(50:4) NL-16:0, D-loopm.16145G>A with TG(54:5) NL-18:0, and D-loopm.16089T>C with PC(16:0_16:1) at the statistically significant threshold of FDR < 0.05. Then, we explored the relationships between mitochondrial genetic variants and traditional lipids, including triglyceride, total cholesterol (TC), low-density lipoprotein cholesterol (LDLC), and high-density lipoprotein cholesterol. Two significant associations were found, namely MT-ND6m.14178T>C with TC and D-loopm.215A>G with LDLC. Furthermore, we performed linear regression analysis to determine on the SNPs of mtDNA and left ventricular ejection fraction (LVEF) and found that the SNP D-loopm.16145G>A was nominally significantly associated with LVEF (P = 0.047). Our findings provide insights into the lipidomic context of mtDNA variations and highlight the importance of studying mitochondrial genetic variants related to lipid species.


Discussion

This work characterizes the cancer mitochondrial genome in a comprehensive manner, including somatic mutations, nuclear transfer, copy number, structural variants and mtDNA gene expression. Because of the ultra-high coverage of mtDNA from the WGS data and the large number of patient samples surveyed, our study provides a definitive landscape of mtDNA somatic mutations and identifies several unique features. First, we report hypermutated mitochondrial cases, highlighting the dynamic mutational processes in this tiny genome. Second, our systemic analysis of mitochondrial genomes has firmly shown that several cancer types are enriched for high-allele-frequency truncating mutations, including previously reported kidney chromophobe 30,45 as well as newly identified kidney papillary, and thyroid and colorectal cancers. Interestingly, the thyroid and kidney are the most frequent sites of oncocytomas, which are rare, benign tumors characterized by frequent nuclear chromosomal aneuploidy as well as vast accumulation of defective mitochondria 45,46 , further assuring the functional association between mitochondrial inactivation and the pathogenesis of these cancer types. Third, in contrast with the diversified mutational signatures observed in the nuclear genomes of different cancers 20 , mtDNAs show very similar mutational signatures regardless of cancer tissue origins: predominantly G>A and T>C substitutions on the L strand. This monotonous pattern may partially stem from different mutational generators and DNA repair processes between the nucleus and mitochondria 9,47,48 . Due to their large numbers of copies per cell, mitochondria may simply remove mtDNA damaged from external mutagens (for example, ultraviolet radiation, tobacco smoking and reactive oxygen species) through autophagy and other mitochondrial dynamic mechanisms 49 , rather than employing a complex array of repair proteins as in the nucleus.

One unique aspect of our study is the integrative analysis of mitochondrial molecular alterations with those in the nuclear genome that are characterized by the PCAWG Consortium. We found that: (1) high-allele-frequency truncating mtDNA mutations are mutually exclusive to mutated cancer genes in kidney cancer (2) mtDNA nuclear transfers are associated with increased numbers of structural variants in the nuclear genome and (3) mtDNA co-expressed nuclear genes are enriched in several processes critical for tumor development. These results indicate that the mitochondrial genome is an essential component in understanding the complex molecular patterns observed in cancer genomes and helping to pinpoint potential cancer driver events. Our results, such as the nuclear transfer of mtDNA into a therapeutic target gene, correlations of mtDNA copy numbers with clinical variables, and the co-expression of mtDNA and clinically actionable genes, underscore the clinical importance of mitochondria.

Taken together, this study has untangled and characterized the full spectrum of molecular alterations of mitochondria in human cancers. Our analyses have provided essentially complete catalogs of somatic mtDNA alterations in cancers, including substitutions, indels, copy-number alterations and structural variants. Furthermore, we have developed a user-friendly web resource to enable the broader biomedical community to capitalize on our results. These efforts lay a foundation for translating mitochondrial biology into clinical investigations.


Variation of Mitochondrial DNA and elite athletic performance

Eri Miyamoto-Mikami , Noriyuki Fuku , in Sports, Exercise, and Nutritional Genomics , 2019

6.6 Summary

Existing literature has demonstrated the association of mtDNA variants/ haplogroups with elite athlete status. However, because these studies have not considered nuclear DNA variants, it is possible that these mtDNA variants/haplogroups are surrogates for nuclear DNA variants that confer the elite athletic performance [hitch-hiking effect ( Bilal et al., 2008 )]. Therefore, we need to consider these associations between mtDNA variants/haplogroups and elite athlete status with caution. To confirm the direct effects of mtDNA variants, functional studies using cybrid cells with identical nuclear DNA but different mtDNA, are important. In the field of sports science, genome-wide analysis such as the genome-wide association study (GWAS) has been introduced ( Ahmetov et al., 2015 Rankinen et al., 2016 ). However, mtDNA variants have often been ignored in the analyses in spite of the importance of mtDNA in mitochondrial function and exercise performance. The influences of the interplay of the mtDNA and nuclear DNA on various phenotypes are clear ( Latorre-Pellicer et al., 2016 ) therefore, concurrent genome-wide analyses (mitochondrial genome and nuclear genome) of elite athletes are required. Thus, consideration of the interactions between mtDNA and nuclear DNA variants will contribute to the elucidation of genetic factors of elite athletic performance.


Three-Parent Babies: The Science of Replacing Mitochondrial DNA and What Remains Unknown

Mitochondrial replacement therapy (MRT) has now been used in humans to conceive a “three-parent baby” to prevent inherited mitochondrial disorders, but there remain questions about the effectiveness of the process.

Last September, the New Hope Fertility Center in New York City announced the birth of a baby boy in Mexico who was conceived through the therapy. A child conceived this way carries the nuclear DNA from two parents as well as the mitochondrial DNA from a second woman who has effectively donated her healthy mitochondria. The technique – which isn’t approved in the U.S. – can help mothers who have defective mitochondrial DNA to avoid passing on the mutations to their children.

Patrick O’Farrell, PhD, professor of biochemistry and biophysics, studies the biology of the mitochondrial genome. His lab uses fruit flies to study how mitochondrial mutations are inherited and what happens when two mitochondrial genomes compete against each other. He answered some questions about what we know and don’t know about MRT.

What is the mitochondrial genome and what does it control?

Mitochondria originated as an intracellular bacterial infection that adapted over billions of years to become an organelle that is often referred to as the powerhouse of the cell. During evolution, the original complexity of the bacteria was greatly reduced and most of the genes were moved to the nucleus. But the transfer of responsibility was not complete and the mitochondrial genome, in most animals, still retains 37 genes.

Patrick O’Farrell, PhD

These 37 genes are essential to the electron transport functions that are the chief energy-providing systems for the body. We know what every one of these genes does in the body, but the final outcome of disruptions to these genes, even when you know what they’re supposed to do, is hard to predict because the body has all sort of regulatory loops that adjust to defects and imbalances.

Unlike the nuclear genome, which is a combination of contributions from both your parents’, you inherit only your mother’s mitochondrial genome. We call the mitochondrial genome the “very lonely genome” because your mitochondrial genome will never encounter another person’s mitochondrial genome. The species is divided every female passes on her mitochondrial genome, and, so long as the female lineage is unbroken, this genome will be passed on, always in isolation. But this lonely genome will accumulate change through mutations. The changes will never be shared, and different changes will accumulate in each female lineage of mitochondrial DNA, so that lineages do diverge over time.

How common are mitochondrial disorders? Would a mother know if she were carrying mutations related to mitochondrial disorders?

The prevalence of maternally inherited mitochondrial disorders is estimated to be roughly 1 in 5,000 adults. Some individuals who carry mutations are relatively healthy, but their children may have a high probability of showing mitochondrial disease—these cases can be very severe with children dying in infancy with wide ranging physical and mental defects.

Mitochondria, shown in a golden color in bovine cells, is often called the power plants of the cell. Image by Torsten Wittmann

The relationship between mutations and symptoms is complex because cells carry many copies of the mitochondrial genome, typically about 1,000. If a person has some copies containing mutations, they can show a range of symptoms whose severity depends on the proportion of functional and defective genomes that they carry.

A mother may not know that she’s at risk of having a child with mitochondrial disease. The inheritance of mitochondrial genomes does not follow the regimented pattern of nuclear genomes, so a mother that is healthy but carries some mitochondrial disease mutations might pass on a higher proportion of mutant genomes to her child.

How is mitochondrial replacement therapy different from gene editing?

In gene editing you’re actually changing the existing genetic code. Mitochondrial replacement therapy is different because there is no change in the DNA. You are just changing the source of the mitochondrial genome. It’s more a kind of transplantation, where you’re rescuing things, like a heart transplant.

If a woman chooses MRT to have children, you would take the nucleus from one of her egg cells, transfer it to a donor egg cell that has had its nucleus removed. The egg cell can be fertilized before or after. So all the nuclear genes come from the parents and it’s the usual two-parent genetics for everything except the 37 genes carried by the mitochondrial genome.

The intention is that all the mitochondrial DNA comes from the donor, but that turns out to be impossible.

Does this really mean that a child born through MRT would have three parents?

It’s true that the baby has three genetic inputs and I have no particular argument with the term “three-parent baby” except it should be clear that they’re tremendously unequal contributors. It’s 99.9 percent normal genetics.

In gene editing you’re actually changing the existing genetic code. Mitochondrial replacement therapy is different because there is no change in the DNA.

One of the concerns with MRT is that some of the maternal mtDNA will be transferred along with the nucleus into the new egg cell and that two mitochondrial genomes will compete with each other. What do we know about this competition?

The new egg cell will have a mix of mitochondrial genomes, maybe 99 percent from the donor and 1 percent from the mother. So the mutant genome is still there, it hasn’t been eliminated, just reduced dramatically.

In our work using fruit flies, we ask how the genomes compete with each other. You’re putting into one arena competitors that have never seen each other before, and genomes are out for themselves. If a genome has a mutation that makes it replicate faster, it has an advantage and takes over – we call these “bully genomes” and they displace “wimpy genomes.”

Our research shows that bully genomes have changes in the regulatory region that control replication. A very small difference in replication rate is positively selected for and can very quickly eliminate a wimpy genome.

Do the consequences of this competition occur during embryonic development or can they occur later in life?

If there were a real “bully-wimp” mismatch situation, I would strongly expect it to show up very early. There is a huge expansion of population of mitochondria during the production of the baby as you age there is not as much growth. During this increase in the population of the mitochondria, a bully genome would have the opportunity to out compete the more slowly replicating genome.

One fact that is pretty clear is that mitochondrial DNA is not completely stable and that you’re constantly making new mitochondrial DNA.

But we think some changes may appear later in life, maybe at a more subtle level. One fact that is pretty clear is that mitochondrial DNA is not completely stable and that you’re constantly making new mitochondrial DNA.

I would strongly predict that this child born in Mexico, who is healthy as an infant and has the vast majority of his mitochondrial DNA from the donor, will go on to do very well.

How might MRT fail and what are some ideas to make MRT more successful?

MRT can provide a wonderful benefit to families carrying such mutations, and the only major concern is that an individual application might fail, not that it is a threat to society and human genetics.

In a recent study using human cells in the lab, 13 out of 15 egg cells after nuclear transfer were dominated by donor mitochondrial DNA, and two reverted to the maternal mitochondrial DNA. That might be good enough to satisfy a lot of parents.

There are two reasonable strategies to make MRT better. The first would be to match donor and maternal mitochondrial genomes. If the genomes are well-matched then the procedure is more likely to have a good outcome. Or, make sure the donor’s is always the bully genome – here there will be a mismatch, but the winner is always the donor’s mitochondrial genome. The later strategy would have the advantage of fully eliminating the mutant genome so that it does not re-emerge in later generations.

These strategies depend on knowing more about the biology of mitochondrial genomes. One of the things we’re trying to figure out is why there are bullies and wimps and how to identify the more powerful replicators. What we’re finding is that this might actually depend on the interplay between nuclear and mitochondrial genes.


The "Central Dogma of Biology"


The idea of protein synthesis is often known as the central dogma since it the most elementary concept required to understand all of biology. All living things undergo the process of protein synthesis. The three major players in the central dogma are DNA, RNA and proteins.


The Original Blueprint - DNA


All living things require a blueprint, a recipe book, to make various essential molecules in our body namely proteins. Like most other organisms, the blueprint for humans is found in the form of DNA which we inherit from our parents. DNA is composed of four molecules known as bases: adenine, thymine, guanine and cytosine (A, T, G and C respectively). Segments of various sequences of these bases are what make up genes. Millions of such bases are found in a copy of DNA, allowing for an almost infinite number of combinations of bases to form genes.

The modified photocopy - RNA


For proteins to be made, information stored in DNA must be first converted into another form. A process known as transcription converts the gene from DNA to RNA, a very similar molecule. This is like photocopying the original blueprint (DNA) onto a different type of paper. Through evolution, the protein making machinery known as the ribosome, can only understand genetic information in the form of RNA.


Depending upon what the gene codes for, the molecules may proceed onto becoming proteins or remain as RNA. The genes that remain as RNA and don’t proceed to become proteins, serve important functions for the cell including helping other RNA molecules in becoming proteins.

The Finished Product - Protein


Proteins are one of the macromolecules, which are essential building blocks of life. A protein is made up of many amino acids bonded together. They are quite abundant in the body, and serve various purposes. Enzymes acting at the molecular level, muscles that move our bodies, hair, nails and eye colour pigment are only a few examples of proteins found in the body.
Information stored in RNA is converted to proteins by a tiny organelle known as a ribosome. This protein making machine reads the sequence of bases in the RNA. This tells the ribosome where the gene starts, stops and what amino acids are required to assemble the protein. This protein is then transported within the cell where it is required. This central dogma of biology is observed in all living things.


Results

The measurement of heteroplasmy from the linear array was found to be reliable compared with conventional sequencing and is illustrated for two previously reported heteroplamsy hotspots, position 16093 ( Figure 1 ) and position 189 ( Figure 2 ). Five of the 37 sites tested were observed to be heteroplasmic.

Two probes signals, 16093 1 and 16093 2, were detected by linear array analysis in the buccal samples but not in the blood of this twin pair, corresponding to 16093 T and C. The relative amounts of the 16093 T and C differed between the twins in the buccal and are reflected both by the intensity of the probe signals (A) as well as the peak height ratio in the sequence chromatogram (B).

Two probe signals were observed within the 189 region corresponding to 189 A and G sequence in both the buccal and blood samples of this twin pair. Similar probe signal intensities and peak heights were observed in the buccal samples. The probe signal and sequence peak corresponding to 189 A was greater in the blood samples compared to the 189.

The mean age, BMI, fasting insulin and glucose serum levels of study subjects and the length and point heteroplasmy counts in buccal swab samples are shown in Table 1 . The overall prevalence of heteroplasmy in both tissues for the polymorphic sites was estimated to be 17%, with prevalence of each of these sites in the 178 buccal swab samples and 165 blood samples is shown in Table 2 .

Table 1

Age (years)BMI (kg/m 2 )Insulin (pmol/l)Glucose (mmol/l)
Heteroplasmy type:HeteroplasmicnMeanSDMeanSDMeanSDMeanSD
Any (control region)N145579.1264.85944.65.10.58
Y33578.9266.75339.85.00.56
Point: HVI (16093)N165579.0264.85945.05.10.59
Y13589.2288.94522.54.90.37
Point: HVII (64 & 189)N174579.0265.25742.45.10.56
Y45110.3312.71558.56.30.35
Length: VRII (523�)N153579.2264.85944.15.10.58
Y25607.1267.55543.15.00.59

Table 2

HeteroplasmyBuccal samples (n =�)Blood samples (n =�)
ynPrevalenceynPrevalencep-value
All sites 3314519%2414115%0.04
HVIall141658%016501.7E-11
16093131657%01650%3.6E-11
16304 to 1632011771%01650-
161110178001650-
16124 to 161290178001650-
163620178001650-
16264 to 162780178001650-
HVIIall41742%41612%0.19
6421761%21631%0.34
18921761%21631%0.34
720178001650-
730178001650-
2000178001650-
2470178001650-
VRI1651901780%01650%-
VRII523 to 5242515314%2214313%0.49
4140178001650-
477 to 4820178001650-
489 to 4930178001650-
523 to 5242515314%2214313%0.49

We compared the rates of heteroplasmy between buccal swab data and blood data from the same individuals and observed no difference in prevalence of heteroplasmy at the VRI, VRII or HVII sites between blood and buccal samples. However, the HVI 16093 point heteroplasmy was observed to be heteroplasmic in buccal swabs, but not blood ( Table 2 ). Heteroplasmy at hypervariable region I (HVI) position 16093 was observed to be 7% in buccal swab samples, but 0% in blood samples with difference in prevalence statistically significant at p =𠂤휐 � . No significant difference was seen between blood and buccal swabs at any of the other sites ( Table 2 ).

For the study assay detection limit (𢏅�%) used to reliably call heteroplasmy, we observed no significant difference in the mean age of heteroplasmic and non-heteroplasmic individuals. However, we did observe that the overall prevalence of heteroplasmy was two-fold higher in the older half of the study subjects compared to the younger half for buccal swabs, blood and in both tissues considered jointly (p =𠂠.03, Table 3 ). When we inspected difference in prevalence by site, we observed that there was marginal statistical evidence (pπ.05) for correlation between age and heteroplasmy at insertion/deletion in positions 523� for both types of tissue ( Table 3 ) with prevalence of heteroplasmy at this site being higher among the older individuals. There was no difference in age at the three other heteroplasmic control region sites.

Table 3

Heteroplasmy Buccal(n =�) Blood(n =�)Pooled(n =�)
Prevalence: Prevalence: Prevalence:
ORpLowerUpperpORpLowerUpperpORpLowerUpperp
All sites
Age1.400.4712%26%0.071.210.919%20%0.121.250.8610%23%0.03
BMI0.680.1023%14%0.130.700.2517%12%0.220.690.1720%13%0.19
Age (adj. BMI)1.280.35 1.311.00 1.000.926
BMI (adj. Age)0.650.10 0.090.660.91 0.210.900.181 0.08
HVI 16093
Age1.500.484%10%0.33--0%0%---2%5%-
BMI0.660.039%6%0.11--0%0%---5%3%-
Age (adj. BMI)1.380.80 -- --
BMI (adj. Age)0.590.02 0.26-- --- -
HVII 64 & 189
Age0.670.302%2%0.870.640.252%2%0.820.660.282%2%0.99
BMI5.350.00030%4%-5.090.00040%5%-5.220.00030%5%-
Age (adj. BMI)0.620.235 0.580.20 0.600.22
BMI (adj. Age)5.420.001 -5.290.001 -5.350.001 -
VRII 523 to 524
Age1.080.025%23%0.011.420.196%21%0.031.520.126%22%0.02
BMI0.590.0818%10%0.030.610.1417%10%0.050.610.1217%10%0.04
Age (adj. BMI)1.840.02 1.620.07 1.730.04
BMI (adj. Age)0.530.05 0.0020.540.08 0.010.530.07 0.004

Heteroplasmic status at the same VRII position (523�) also appeared to be more strongly associated with age when considered in conjunction with BMI using multiple regression. This was true for buccal, blood and combined tissue analyses (p =𠂠.004, Table 3 ) with prevalence of heteroplasmy increasing between the lower and upper median quantiles of age (6% vs 22%), but decreasing with BMI median quantiles (17% versus 10%). For combined tissue analyses, the adjusted odds ratio (OR) for heteroplasmy at position 523� was 1.7 for each quartile increment in age and OR =𠂠.5 per quartile increment in BMI (p =𠂠.03, Table 3 ), while for the corresponding estimates for dichotomised age and BMI (not shown) were OR =𠂥.4 and OR =𠂠.3, respectively (p =𠂠.004 pseudo-R 2  =𠂠.11. The latter indicates that BMI and age jointly account for approximately 11% of the variance in heteroplasmy liability at VRII 523�).

BMI was also associated with heteroplasmy at HVII, while age was not. Although the numbers of individuals observed to be heteroplasmic at HVII (sites 64 and 189) were low (n =𠂤), these individuals showed a large mean increase in BMI (4.3 kg/m 2 , p =𠂠.001) and fasting insulin (98.1 pmol/l, p =𠂥휐 𢄦 , Table 4 ) and glucose (1.2 mmol/l, p =𠂤휐 𢄥 , Table 4 ) serum levels. The prevalence of heteroplasmy at this site was zero for the lower quartile and approximately 3% in the upper quartile for all three traits ( Table 4 ). All four individuals were over-weight (BMI 28�) and showed signs of insulin resistance (as measured by minimum fasting insulin𾅈 pmol/l and glucoseϦ mmol/l), but their mean age was no different to non-heteroplasmic individuals at HVII.

Table 4

HeteroplasmyBuccal (n =�)Blood (n =�)Pooled samples (n =�)
Prevalence: Prevalence: Prevalence:
βpLowerUpperβpLowerUpperβpLowerUpper
All sites
Insulin𢄦.20.6519%11%𢄣.50.8415%8%𢄥.00.7417%10%
Glucose𢄠.10.5420%12%𢄠.10.7814%11%𢄠.10.6517%11%
IGR𢄡.40.5317%13%𢄡.00.6915%8%𢄡.20.6016%11%
IGR (adj. for ageʻMI)𢄡.00.62 𢄡.10.65 𢄡.10.62
HVI 16093
Insulin�.10.178%6%--0%0%�.70.174%3%
Glucose𢄠.20.1610%3%--0%0%𢄠.20.165%2%
IGR𢄢.30.216%8%--0%0%𢄢.20.213%4%
IGR (adj. for ageʻMI)𢄢.90.20 -- 𢄢.90.19
HVII 64 & 189
Insulin98.10.0010%3%98.10.0020%3%98.15.E-060%3%
Glucose1.20.0040%3%1.20.0050%4%1.24.E-050%3%
IGR13.80.010%3%13.80.0170%3%13.80.0010%3%
IGR (adj. for ageʻMI)11.30.04 11.20.04 11.20.003
VRII 523 to 524
Insulin𢄤.10.7916%10%𢄣.50.8415%8%𢄣.80.8215%9%
Glucose𢄠.10.7415%12%𢄠.10.7814%11%𢄠.10.7615%11%
IGR𢄡.10.6416%9%𢄡.00.6915%8%𢄡.10.6615%9%
IGR (adj. for ageʻMI)𢄡.00.67 𢄡.10.65 𢄡.10.65

Association of position 16093 with heteroplasmy

In this study we observe blood data, which are not heteroplasmic at position 16093, and buccal swab data, which are heteroplasmic at this site. We find that the presence of the C allele at 16093 in blood mtDNA is strongly associated with the presence of heteroplasmy in buccal samples at the same HVI site ( Table 5 ). In addition the C allele at HVI 16093 in blood is also associated with heteroplasmy at VRII for both buccal and blood samples ( Table 5 ). The relative risk of being heteroplasmic at VRII 523� for those with a C allele at 16093 is approximately six times those with a T allele ( Table 5 ).

Table 5

Heteroplasmy: At any site HVI (16093)HVII (64 & 189)VRII (523�)
TissueN(%)Y(%)OR(95% CI)pN(%)Y(%)pN(%)Y(%)pN(%)Y(%)OR(95% CI)p
Allele at 16093 in blood Buccal
T 134(88)19(12)-4.6E-09153(100)0(0)3.5E-14149(97)4(3)0.50136(89)17(11)16.0(3.0�.0)0.0002
C 0(0)9(100) 1(11)8(89) 9(100)0(0) 3(33)6(67)
Blood
T 134(88)19(12)11.2(3.0�.0)0.0006153(100)0(0) 149(97)4(3)0.47136(89)17(11)12.8(3.0�.0)3.1E-04
C 4(40)6(60) 10(100)0(0) 10(100)0(0) 4(40)6(60)

Twin concordance: MZ twins were completely (100%) concordant for total heteroplasmy status in the control region. The DZ case-wise concordance was found to be 94.1% (95% CI 83%�%), with only one pair discordant for heteroplasmy in the control region. We used bootstrap methods to empirically assess whether this slight difference in concordance between MZ and DZ twins was statistically significant and observed the difference not to differ significantly from zero (5.9%, 95% CI: 𢄧.3%�.1% pπ.38).


New molecular tool precisely edits mitochondrial DNA

The genome in mitochondria -- the cell's energy-producing organelles -- is involved in disease and key biological functions, and the ability to precisely alter this DNA would allow scientists to learn more about the effects of these genes and mutations. But the precision editing technologies that have revolutionized DNA editing in the cell nucleus have been unable to reach the mitochondrial genome.

Now, a team at the Broad Institute of MIT and Harvard and the University of Washington School of Medicine has broken this barrier with a new type of molecular editor that can make precise C* G-to-T* A nucleotide changes in mitochondrial DNA. The editor, engineered from a bacterial toxin, enables modeling of disease-associated mitochondrial DNA mutations, opening the door to a better understanding of genetic changes associated with cancer, aging, and more.

The work is described in Nature, with co-first authors Beverly Mok, a graduate student from the Broad Institute and Harvard University, and Marcos de Moraes, a postdoctoral fellow at the University of Washington (UW).

The work was jointly supervised by Joseph Mougous, UW professor of microbiology and an investigator at the Howard Hughes Medical Institute (HHMI), and David Liu, the Richard Merkin Professor and director of the Merkin Institute of Transformative Technologies in Healthcare at the Broad Institute, professor of chemistry and chemical biology at Harvard University, and HHMI investigator.

"The team has developed a new way of manipulating DNA and used it to precisely edit the human mitochondrial genome for the first time, to our knowledge -- providing a solution to a long-standing challenge in molecular biology," said Liu. "The work is a testament to collaboration in basic and applied research, and may have further applications beyond mitochondrial biology."

Agent of bacterial warfare

Most current approaches to studying specific variations in mitochondrial DNA involve using patient-derived cells, or a small number of animal models, in which mutations have occurred by chance. "But these methods pose major limitations, and creating new, defined models has been impossible," said co-author Vamsi Mootha, institute member and co-director of the Metabolism Program at Broad. Mootha is also an HHMI investigator and professor of medicine at Massachusetts General Hospital.

While CRISPR-based technologies can rapidly and precisely edit DNA in the cell nucleus, greatly facilitating model creation for many diseases, these tools haven't been able to edit mitochondrial DNA because they rely on a guide RNA to target a location in the genome. The mitochondrial membrane allows proteins to enter the organelle, but is not known to have accessible pathways for transporting RNA.

One piece of a potential solution arose when the Mougous lab identified a toxic protein made by the pathogen Burkholderia cenocepacia. This protein can kill other bacteria by directly changing cytosine (C) to uracil (U) in double-stranded DNA.

"What is special about this protein, and what suggested to us that it might have unique editing applications, is its ability to target double-stranded DNA. All previously described deaminases that target DNA work only on the single-stranded form, which limits how they can be used as genome editors," said Mougous. His team determined the structure and biochemical characteristics of the toxin, called DddA.

"We realized that the properties of this 'bacterial warfare agent' could allow it to be paired with a non-CRISPR-based DNA-targeting system, raising the possibility of making base editors that do not rely on CRISPR or on guide RNAs," explained Liu. "It could enable us to finally perform precision genome editing in one of the last corners of biology that has remained untouchable by such technology -- mitochondrial DNA."

"Taming the beast"

The team's first major challenge was to eliminate the toxicity of the bacterial agent -- what Liu described to Mougous as "taming the beast" -- so that it could edit DNA without damaging the cell. The researchers divided the protein into two inactive halves that could edit DNA only when they combined.

The researchers tethered the two halves of the tamed bacterial toxin to TALE DNA-binding proteins, which can locate and bind a target DNA sequence in both the nucleus and mitochondria without the use of a guide RNA. When these pieces bind DNA next to each other, the complex reassembles into its active form, and converts C to U at that location -- ultimately resulting in a C* G-to-T* A base edit. The researchers called their tool a DddA-derived cytosine base editor (DdCBE).

The team tested DdCBE on five genes in the mitochondrial genome in human cells and found that DdCBE installed precise base edits in up to 50 percent of the mitochondrial DNA. They focused on the gene ND4, which encodes a subunit of the mitochondrial enzyme complex I, for further characterization. Mootha's lab analyzed the mitochondrial physiology and chemistry of the edited cells and showed that the changes affected mitochondria as intended.

"This is the first time in my career that we've been able to engineer a precise edit in mitochondrial DNA," said Mootha. "It's a quantum leap forward -- if we can make targeted mutations, we can develop models to study disease-associated variants, determine what role they actually play in disease, and screen the effects of drugs on the pathways involved."

Future developments

One goal for the field now will be to develop editors that can precisely make other types of genetic changes in mitochondrial DNA.

"A mitochondrial genome editor has the long-term potential to be developed into a therapeutic to treat mitochondrial-derived diseases, and it has more immediate value as a tool that scientists can use to better model mitochondrial diseases and explore fundamental questions pertaining to mitochondrial biology and genetics," Mougous said.

The team added that some features of DdCBE, such as its lack of RNA, may also be attractive for other gene-editing applications beyond the mitochondria.

This work was supported in part by the Merkin Institute of Transformative Technologies in Healthcare, NIH (R01AI080609, U01AI142756, RM1HG009490, R35GM122455, R35GM118062, and P30DK089507), Defense Threat Reduction Agency (1-13-1-0014), and University of Washington Cystic Fibrosis Foundation


Claire and Jacob1.jpeg

Leigh syndrome is a name for a severe and sometimes life-limiting mitochondrial disease, which can have many different genetic causes. It can be caused by mutations in mitochondrial DNA, but around 80% of cases are caused by mutations in the DNA in the nucleus. When we talk about a clinical diagnosis, we mean the diagnosis based on symptoms - in this case, Leigh Syndrome. A genetic diagnosis is finding the single variant that is causing Leigh Syndrome in that patient, which could be in any of the >75 genes associated with the disease.

Frankie - Before you went through the process of trying to find a genetic diagnosis, what were you expecting? Did you think that the first test would give you an answer, or did you know there was some uncertainty?

Claire - I do have a background in biology, I knew what mitochondria were, which was a start! So I understood that there was a chance we wouldn’t find anything, but I hoped that we would. I do think there is a level of misunderstanding - some people think that you guys in the lab are like gods and just know everything which, unfortunately, is not true - and I think that’s what sometimes causes disappointment.

Frankie - One of the things we’re told when we’re training is that a genetic diagnosis is the most important thing for patients and their families, from your experience, how important is it?

Claire - I think that having genetic diagnosis might have made it easier to accept that Jacob had mitochondrial disease, but it wouldn’t have made a difference to him. I think some people believe that having a genetic diagnosis might change the outcome, but it doesn’t if there’s no cure. The main reason you want to know is if you want to have more children. I still think it’s incredibly important as it might help with research in years to come, but at the moment a genetic diagnosis will not change what happens to your child.

For us, we did still have that clinical diagnosis, we knew it was mitochondrial disease and that meant we could contact the Lily Foundation. We were still dealing with something that was horrific, but we were part of a community that understood it - some families don’t even get that.

If a family has a known genetic diagnosis, there are many reproductive options out there for them. They can have a prenatal diagnosis, where we test the amniotic fluid for the mutation, and this can be offered on the NHS. But without knowing what we’re looking for, we can’t do those tests.

Claire - So there was no option of a prenatal diagnosis, but we did still want another child. I mean, Jacob was never able to give me a cuddle, or give me a kiss, or say ‘mummy’. I wanted the chance of a child who could do those things, which is true for most parents. We spoke to a genetic counsellor at Great Ormond Street and were told there was probably a 1 in 4 chance of having another affected child. So we decided it was worth a try, we ‘rolled the dice’, and we had a healthy daughter, Charlotte in March 2017.

The Lily Foundation is a mitochondrial disease charity. They support families by holding annual meet-up events, helping pay for specialist care equipment and funding short leisure breaks. They also raise awareness about mitochondrial disease and raise money to fund research into new tests and treatments.

Frankie - Some scientists in my department are working on an exciting project called Next Generation Children, where they do rapid whole genome sequencing of babies in intensive care in as little as 4 weeks. This means that parents might know sooner whether the disease can be cured or not. How do you think something like that would have affected you and your family?

Claire - I think it would have made a huge difference. When I look back, I feel that we did what was right for us and our baby at the time, but perhaps if there was less going on, fewer tests and procedures, I might have enjoyed my time with him more. He had two eye operations, that in the end he didn’t need, and maybe we would have moved over to hospice care a lot sooner. We could have had more time to just cuddle him, and when you only have 501 days with your child, a couple more days of just cuddling would have been lovely.

Frankie - So finally, what advice would you give someone like me who works in the lab, never sees patients, who are normally just a tube or a number on a screen to me - how can we keep the patient in our mind?

Claire - I think that, if you can, doing something like volunteering with children and families affected by genetic disease would make a massive difference. And I think it would be amazing for people like you to have the opportunity to go and volunteer somewhere or talk to someone like me to get an idea of what we go through. It’s also a really good way of raising awareness - which is why charities like the Lily Foundation are so important. Without awareness there’s no funding, without funding there’s no research and without research there’ll be no cure. And it might give you a better understanding how important the work you do is - and what a responsibility you have. In a way you’re holding peoples’ hopes and dreams in your hands - and we’re all really grateful that you’ve chosen to do that.

What my experience talking to Claire 1 showed me is that, as geneticists, we need to descend from our ivory tower, go out there and meet the people whose lives our work can change so dramatically. I think this is true for all scientists, including researchers, as we can spread the word about the amazing work we are doing whilst learning more about its real-life effects. As for me, when I’m feeling bogged-down by a data overload, unable to see the wood for the genes, I'll think of Claire and Jacob and of their journey through the genetic wilderness. Knowing that each line in my spreadsheet could give this patient or family the answer they are looking for is worth all the stale cake in the world.