Genetic Chimerism: Marmosets contain multitudes
Single-cell RNA sequencing reveals the extent to which marmosets carry genetically distinct cells from their siblings.
-
Download
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Genetic Chimerism: Marmosets contain multitudeseLife 13:e97866.https://doi.org/10.7554/eLife.97866 - Cite
- CommentOpen annotations (there are currently 0 annotations on this page).
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, United States
Marmosets almost always produce non-identical twins which, unusually, share much more than just a womb. The same circulatory system connects the siblings during pregnancy, allowing two genetically distinct individuals to freely exchange the hematopoietic stem cells that give rise to all blood and immune cells (Gengozian et al., 1969; Wislocki, 1939; Hill, 1932). As a result, a drop of blood from this tiny South American primate reveals a mixture of cells originating from each twin (Benirschike and Brownhill, 1962). This is known as sibling chimerism – from Chimera, the monster from Greek mythology that is a hybrid of a lion, a goat and other creatures.
This quirk of nature has been known for decades (Benirschke et al., 1962). Yet, while studies have detected genetic information from the other twin in certain organs, it has remained difficult to precisely test whether sibling chimerism is limited to blood-related cells or extends to other cell types (Sweeney et al., 2012; Ross et al., 2007). Answering this question would help to uncover how cellular exchange takes place between marmoset twins, while also allowing researchers to investigate how genetic variations affect cell function in vivo. However, this requires technology that has only become recently available, and which makes it possible to isolate and sequence the genetic material of individual cells in a single tissue. If different genomes are identified in a heart sample, for example, these newer approaches can now distinguish whether they originate from the muscle cells of the heart, the blood cells pumped through it, or the resident immune cells that protect it. Now, in eLife, Ricardo del Rosario, Steven McCarroll and colleagues at Harvard Medical School, the Broad Institute and MIT report having addressed this knowledge gap by applying single-cell sequencing to various marmoset organs (del Rosario et al., 2024).
Rather than focusing on DNA, the team took advantage of the thousands of genetic variants transcribed into RNAs and opted instead for single-nucleus RNA-sequencing. Being able to capture all the genes being transcribed in an individual cell did double duty. del Rosario et al. could identify which tissues contained cells from the other twin; and they could also examine the impact of these genetic differences on gene expression patterns and cell function.
To investigate the first question, the team tested for sibling chimerism in the blood, liver, kidney and brain – all tissues which contain varying amounts of cell types deriving from hematopoietic stem cells. This confirmed that chimerism is prevalent and widespread in marmosets, while also allowing del Rosario et al. to precisely identify which cells were from the sampled individual, and which were from its twin. In doing so, they demonstrated that sibling chimerism is limited to cells from the two lineages (myeloid and lymphoid) that hematopoietic stem cells give rise to. Across the organs studied, all the other cell types examined originated from the twin being sampled (Figure 1).
Figure 1
Investigating sibling chimerism in marmosets.
Marmosets almost always produce non-identical twins (also known as fraternal or dizygotic twins). However, these siblings are more alike than expected because they share a circulatory system in the …
The team then turned its attention to microglia, the primary immune cells of the brain, using a single-nucleus RNA-sequencing dataset of more than 2.2 million cells from various brain regions of 11 marmosets (Krienen et al., 2023). Consistent with the findings for non-brain tissues, this analysis first revealed that the proportion of sibling-derived microglia varies between the brain areas of an individual. del Rosario et al. suggest two possible explanations for this finding: (1) Such variations may be due to cell migration and proliferation taking place in a random manner, with the level of sibling-derived cells reflecting which cells arrived first and multiplied the most in a tissue. (2) Alternatively, cells from the twin may be recruited and proliferate differently across brain tissues and even local environments due to their genetic background.
To then test if genetic variations between cells could indeed impact their expression patterns, del Rosario et al. directly compared how microglia in the same brain region expressed their genes depending on whether they were from the sampled animal or its twin. When assessing if cells facing the same constraints respond differently because of variations in their genomes, this is as environmentally controlled a study can get in a living animal – nature’s very own common garden experiment, where scientists examine how populations of different genetic origins fare when facing the same conditions. The results show that the local environment, such as which brain region the cells were in, had a much larger impact in shaping gene expression than the genetic background. This does not indicate that genetic variation is unimportant, but it does highlight how cells – no matter who they come from – are very good at doing their job when they find themselves in the right place at the right time.
All told, this thoughtful and thorough study accomplishes two important goals. First, it all but closes a previously open question on the extent and cell origins of sibling chimerism. Second, it sets the stage for using this unique model system to examine, in a natural context, how genetic variation in microglia may impact brain development, function, and disease.
References
-
Further observations on marrow chimerism in marmosetsCytogenetics 1:245–257.https://doi.org/10.1159/000129734
-
The developmental history of the primatesPhilosophical Transactions of the Royal Society of London. Series B 221:45–178.https://doi.org/10.1098/rstb.1932.0002
-
Observations on twinning in marmosetsAmerican Journal of Anatomy 64:445–483.https://doi.org/10.1002/aja.1000640305
Article and author information
Author details
Noah Snyder-Mackler
Publication history
Copyright
© 2024, Chiou and Snyder-Mackler
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 526
- views
-
- 33
- downloads
-
- 0
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Further reading
-
- Computational and Systems Biology
- Genetics and Genomics
Obesity is a major risk factor for type 2 diabetes, dyslipidemia, cardiovascular disease, and hypertension. Intriguingly, there is a subset of metabolically healthy obese (MHO) individuals who are seemingly able to maintain a healthy metabolic profile free of metabolic syndrome. The molecular underpinnings of MHO, however, are not well understood. Here, we report that CTRP10/C1QL2-deficient mice represent a unique female model of MHO. CTRP10 modulates weight gain in a striking and sexually dimorphic manner. Female, but not male, mice lacking CTRP10 develop obesity with age on a low-fat diet while maintaining an otherwise healthy metabolic profile. When fed an obesogenic diet, female Ctrp10 knockout (KO) mice show rapid weight gain. Despite pronounced obesity, Ctrp10 KO female mice do not develop steatosis, dyslipidemia, glucose intolerance, insulin resistance, oxidative stress, or low-grade inflammation. Obesity is largely uncoupled from metabolic dysregulation in female KO mice. Multi-tissue transcriptomic analyses highlighted gene expression changes and pathways associated with insulin-sensitive obesity. Transcriptional correlation of the differentially expressed gene (DEG) orthologs in humans also shows sex differences in gene connectivity within and across metabolic tissues, underscoring the conserved sex-dependent function of CTRP10. Collectively, our findings suggest that CTRP10 negatively regulates body weight in females, and that loss of CTRP10 results in benign obesity with largely preserved insulin sensitivity and metabolic health. This female MHO mouse model is valuable for understanding sex-biased mechanisms that uncouple obesity from metabolic dysfunction.
-
- Genetics and Genomics
- Neuroscience
The mammalian suprachiasmatic nucleus (SCN), situated in the ventral hypothalamus, directs daily cellular and physiological rhythms across the body. The SCN clockwork is a self-sustaining transcriptional-translational feedback loop (TTFL) that in turn coordinates the expression of clock-controlled genes (CCGs) directing circadian programmes of SCN cellular activity. In the mouse, the transcription factor, ZFHX3 (zinc finger homeobox-3), is necessary for the development of the SCN and influences circadian behaviour in the adult. The molecular mechanisms by which ZFHX3 affects the SCN at transcriptomic and genomic levels are, however, poorly defined. Here, we used chromatin immunoprecipitation sequencing to map the genomic localization of ZFHX3-binding sites in SCN chromatin. To test for function, we then conducted comprehensive RNA sequencing at six distinct times-of-day to compare the SCN transcriptional profiles of control and ZFHX3-conditional null mutants. We show that the genome-wide occupancy of ZFHX3 occurs predominantly around gene transcription start sites, co-localizing with known histone modifications, and preferentially partnering with clock transcription factors (CLOCK, BMAL1) to regulate clock gene(s) transcription. Correspondingly, we show that the conditional loss of ZFHX3 in the adult has a dramatic effect on the SCN transcriptome, including changes in the levels of transcripts encoding elements of numerous neuropeptide neurotransmitter systems while attenuating the daily oscillation of the clock TF Bmal1. Furthermore, various TTFL genes and CCGs exhibited altered circadian expression profiles, consistent with an advanced in daily behavioural rhythms under 12 h light–12 h dark conditions. Together, these findings reveal the extensive genome-wide regulation mediated by ZFHX3 in the central clock that orchestrates daily timekeeping in mammals.
