scholarly journals Widespread haploid-biased gene expression enables sperm-level natural selection

Science ◽  
2021 ◽  
pp. eabb1723
Author(s):  
Kunal Bhutani ◽  
Katherine Stansifer ◽  
Simina Ticau ◽  
Lazar Bojic ◽  
Alexandra-Chloé Villani ◽  
...  

Sperm are haploid, but must be functionally equivalent to distribute alleles equally among progeny. Accordingly, gene products are shared through spermatid cytoplasmic bridges which erase phenotypic differences between individual haploid sperm. Here, we show that a large class of mammalian genes are not completely shared across these bridges. We term these genes “genoinformative markers” (GIMs) and show that a subset can act as selfish genetic elements that spread alleles unevenly through murine, bovine, and human populations. We identify evolutionary pressure to avoid conflict between sperm and somatic function as GIMs are enriched for testis-specific gene expression, paralogs, and isoforms. Therefore, GIMs and sperm-level natural selection may help explain why testis gene expression patterns are an outlier relative to all other tissues.

2019 ◽  
Author(s):  
Kunal Bhutani ◽  
Katherine Stansifer ◽  
Simina Ticau ◽  
Lazar Bojic ◽  
Chloe Villani ◽  
...  

1AbstractMendel’s first law dictates that alleles segregate randomly during meiosis and are distributed to offspring with equal frequency, requiring sperm to be functionally independent of their genetic payload. Developing mammalian spermatids have been thought to accomplish this by freely sharing RNA from virtually all genes through cytoplasmic bridges, equalizing allelic gene expression across different genotypes. Applying single cell RNA sequencing to developing spermatids, we identify a large class of mammalian genes whose allelic expression ratio is informative of the haploid genotype, which we call genoinformative markers (GIMs). 29% of spermatid-expressed genes in mice and 47% in non-human primates are not uniformly shared, and instead show a confident allelic expression bias of at least 2-fold towards the haploid genotype. This property of GIMs was significantly conserved between individuals and between rodents and primates. Consistent with the interpretation of specific RNA localization resulting in incomplete sharing through cytoplasmic bridges, we observe a strong depletion of GIM transcripts from chromatoid bodies, structures involved in shuttling RNA across cytoplasmic bridges, and an enrichment for 3’ UTR motifs involved in RNA localization. If GIMs are translated and functional in the context of fertility, they would be able to violate Mendel’s first law, leading to selective sweeps through a population. Indeed, we show that GIMs are enriched for signatures of positive selection, accounting for dozens of recent mouse, human, and primate selective sweeps. Intense selection at the sperm level risks evolutionary conflict between germline and somatic function, and GIMs show evidence of avoiding this conflict by exhibiting more testis-specific gene expression, paralogs, and isoforms than expression-matched control genes. The widespread existence of GIMs suggests that selective forces acting at the level of individual mammalian sperm are much more frequent than commonly believed.2Author’s summaryMendel’s first law dictates that alleles are distributed to offspring with equal frequency, requiring sperm carrying different genetics to be functionally equivalent. Despite a small number of known exceptions to this, it is widely believed that sharing of gene products through cytoplasmic bridges erases virtually all differences between haploid sperm. Here, we show that a large class of mammalian genes are not completely shared across these bridges, therefore causing sperm phenotype to correspond partly to haploid genotype. We term these genes “genoinformative markers” (GIMs) and show that their identity tends to be conserved from rodents to primates. Because some GIMs can link sperm genotype to function, they can be thought of as selfish genetic elements which lead to natural selection between sperm rather than between organisms, a violation of Mendel’s first law. We find evidence of this biased inheritance, showing that GIMs are strongly enriched for selective sweeps that spread alleles through mouse and human populations. For genes expressed both in sperm and in somatic tissues, this can cause a conflict because optimizing gene function for sperm may be detrimental to its other functions. We show that there is evolutionary pressure to avoid this conflict, as GIMs are strongly enriched for testis-specific gene expression, testis-specific paralogs, and testis-specific isoforms. Therefore, GIMs and sperm-level natural selection may provide an elegant explanation for the peculiarity of testis gene expression patterns, which are an extreme outlier relative to all other tissues.


2021 ◽  
pp. 002203452110120
Author(s):  
C. Gluck ◽  
S. Min ◽  
A. Oyelakin ◽  
M. Che ◽  
E. Horeth ◽  
...  

The parotid, submandibular, and sublingual glands represent a trio of oral secretory glands whose primary function is to produce saliva, facilitate digestion of food, provide protection against microbes, and maintain oral health. While recent studies have begun to shed light on the global gene expression patterns and profiles of salivary glands, particularly those of mice, relatively little is known about the location and identity of transcriptional control elements. Here we have established the epigenomic landscape of the mouse submandibular salivary gland (SMG) by performing chromatin immunoprecipitation sequencing experiments for 4 key histone marks. Our analysis of the comprehensive SMG data sets and comparisons with those from other adult organs have identified critical enhancers and super-enhancers of the mouse SMG. By further integrating these findings with complementary RNA-sequencing based gene expression data, we have unearthed a number of molecular regulators such as members of the Fox family of transcription factors that are enriched and likely to be functionally relevant for SMG biology. Overall, our studies provide a powerful atlas of cis-regulatory elements that can be leveraged for better understanding the transcriptional control mechanisms of the mouse SMG, discovery of novel genetic switches, and modulating tissue-specific gene expression in a targeted fashion.


2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Floranne Boulogne ◽  
Laura Claus ◽  
Henry Wiersma ◽  
Roy Oelen ◽  
Floor Schukking ◽  
...  

Abstract Background and Aims Genetic testing in patients with suspected hereditary kidney disease does not always reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes that are not known to be involved in kidney disease, which makes it difficult to prioritize and interpret the relevance of these variants. As such, there is a clear need for methods that predict the phenotypic consequences of gene expression in a way that is as unbiased as possible. To help identify candidate genes we have developed KidneyNetwork, in which tissue-specific expression is utilized to predict kidney-specific gene functions. Method We combined gene co-expression in 878 publicly available kidney RNA-sequencing samples with the co-expression of a multi-tissue RNA-sequencing dataset of 31,499 samples to build KidneyNetwork. The expression patterns were used to predict which genes have a kidney-related function, and which (disease) phenotypes might be caused when these genes are mutated. By integrating the information from the HPO database, in which known phenotypic consequences of disease genes are annotated, with the gene co-expression network we obtained prediction scores for each gene per HPO term. As proof of principle, we applied KidneyNetwork to prioritize variants in exome-sequencing data from 13 kidney disease patients without a genetic diagnosis. Results We assessed the prediction performance of KidneyNetwork by comparing it to GeneNetwork, a multi-tissue co-expression network we previously developed. In KidneyNetwork, we observe a significantly improved prediction accuracy of kidney-related HPO-terms, as well as an increase in the total number of significantly predicted kidney-related HPO-terms (figure 1). To examine its clinical utility, we applied KidneyNetwork to 13 patients with a suspected hereditary kidney disease without a genetic diagnosis. Based on the HPO terms “Renal cyst” and “Hepatic cysts”, combined with a list of potentially damaging variants in one of the undiagnosed patients with mild ADPKD/PCLD, we identified ALG6 as a new candidate gene. ALG6 bears a high resemblance to other genes implicated in this phenotype in recent years. Through the 100,000 Genomes Project and collaborators we identified three additional patients with kidney and/or liver cysts carrying a suspected deleterious variant in ALG6. Conclusion We present KidneyNetwork, a kidney specific co-expression network that accurately predicts what genes have kidney-specific functions and may result in kidney disease. Gene-phenotype associations of genes unknown for kidney-related phenotypes can be predicted by KidneyNetwork. We show the added value of KidneyNetwork by applying it to exome sequencing data of kidney disease patients without a molecular diagnosis and consequently we propose ALG6 as a promising candidate gene. KidneyNetwork can be applied to clinically unsolved kidney disease cases, but it can also be used by researchers to gain insight into individual genes to better understand kidney physiology and pathophysiology. Acknowledgments This research was made possible through access to the data and findings generated by the 100,000 Genomes Project; http://www.genomicsengland.co.uk.


1992 ◽  
Vol 4 (11) ◽  
pp. 1383-1404 ◽  
Author(s):  
G N Drews ◽  
T P Beals ◽  
A Q Bui ◽  
R B Goldberg

2019 ◽  
Vol 104 (11) ◽  
pp. 5225-5237 ◽  
Author(s):  
Mariam Haffa ◽  
Andreana N Holowatyj ◽  
Mario Kratz ◽  
Reka Toth ◽  
Axel Benner ◽  
...  

Abstract Context Adipose tissue inflammation and dysregulated energy homeostasis are key mechanisms linking obesity and cancer. Distinct adipose tissue depots strongly differ in their metabolic profiles; however, comprehensive studies of depot-specific perturbations among patients with cancer are lacking. Objective We compared transcriptome profiles of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) from patients with colorectal cancer and assessed the associations of different anthropometric measures with depot-specific gene expression. Design Whole transcriptomes of VAT and SAT were measured in 233 patients from the ColoCare Study, and visceral and subcutaneous fat area were quantified via CT. Results VAT compared with SAT showed elevated gene expression of cytokines, cell adhesion molecules, and key regulators of metabolic homeostasis. Increased fat area was associated with downregulated lipid and small molecule metabolism and upregulated inflammatory pathways in both compartments. Comparing these patterns between depots proved specific and more pronounced gene expression alterations in SAT and identified unique associations of integrins and lipid metabolism–related enzymes. VAT gene expression patterns that were associated with visceral fat area poorly overlapped with patterns associated with self-reported body mass index (BMI). However, subcutaneous fat area and BMI showed similar associations with SAT gene expression. Conclusions This large-scale human study demonstrates pronounced disparities between distinct adipose tissue depots and reveals that BMI poorly correlates with fat mass–associated changes in VAT. Taken together, these results provide crucial evidence for the necessity to differentiate between distinct adipose tissue depots for a correct characterization of gene expression profiles that may affect metabolic health of patients with colorectal cancer.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Stuart P. Wilson ◽  
Sebastian S. James ◽  
Daniel J. Whiteley ◽  
Leah A. Krubitzer

AbstractDevelopmental dynamics in Boolean models of gene networks self-organize, either into point attractors (stable repeating patterns of gene expression) or limit cycles (stable repeating sequences of patterns), depending on the network interactions specified by a genome of evolvable bits. Genome specifications for dynamics that can map specific gene expression patterns in early development onto specific point attractor patterns in later development are essentially impossible to discover by chance mutation alone, even for small networks. We show that selection for approximate mappings, dynamically maintained in the states comprising limit cycles, can accelerate evolution by at least an order of magnitude. These results suggest that self-organizing dynamics that occur within lifetimes can, in principle, guide natural selection across lifetimes.


2020 ◽  
Vol 117 (29) ◽  
pp. 17031-17040 ◽  
Author(s):  
Allegra Terhorst ◽  
Arzu Sandikci ◽  
Abigail Keller ◽  
Charles A. Whittaker ◽  
Maitreya J. Dunham ◽  
...  

Aneuploidy, a condition characterized by whole chromosome gains and losses, is often associated with significant cellular stress and decreased fitness. However, how cells respond to the aneuploid state has remained controversial. In aneuploid budding yeast, two opposing gene-expression patterns have been reported: the “environmental stress response” (ESR) and the “common aneuploidy gene-expression” (CAGE) signature, in which many ESR genes are oppositely regulated. Here, we investigate this controversy. We show that the CAGE signature is not an aneuploidy-specific gene-expression signature but the result of normalizing the gene-expression profile of actively proliferating aneuploid cells to that of euploid cells grown into stationary phase. Because growth into stationary phase is among the strongest inducers of the ESR, the ESR in aneuploid cells was masked when stationary phase euploid cells were used for normalization in transcriptomic studies. When exponentially growing euploid cells are used in gene-expression comparisons with aneuploid cells, the CAGE signature is no longer evident in aneuploid cells. Instead, aneuploid cells exhibit the ESR. We further show that the ESR causes selective ribosome loss in aneuploid cells, providing an explanation for the decreased cellular density of aneuploid cells. We conclude that aneuploid budding yeast cells mount the ESR, rather than the CAGE signature, in response to aneuploidy-induced cellular stresses, resulting in selective ribosome loss. We propose that the ESR serves two purposes in aneuploid cells: protecting cells from aneuploidy-induced cellular stresses and preventing excessive cellular enlargement during slowed cell cycles by down-regulating translation capacity.


Author(s):  
Harikrishna Nakshatri ◽  
Sunil Badve

Breast cancer is a heterogeneous disease and classification is important for clinical management. At least five subtypes can be identified based on unique gene expression patterns; this subtype classification is distinct from the histopathological classification. The transcription factor network(s) required for the specific gene expression signature in each of these subtypes is currently being elucidated. The transcription factor network composed of the oestrogen (estrogen) receptor α (ERα), FOXA1 and GATA3 may control the gene expression pattern in luminal subtype A breast cancers. Breast cancers that are dependent on this network correspond to well-differentiated and hormone-therapy-responsive tumours with good prognosis. In this review, we discuss the interplay between these transcription factors with a particular emphasis on FOXA1 structure and function, and its ability to control ERα function. Additionally, we discuss modulators of FOXA1 function, ERα–FOXA1–GATA3 downstream targets, and potential therapeutic agents that may increase differentiation through FOXA1.


2008 ◽  
Vol 180 (1) ◽  
pp. 45-56 ◽  
Author(s):  
Nadia Goué ◽  
Marie-Claude Lesage-Descauses ◽  
Ewa J. Mellerowicz ◽  
Elisabeth Magel ◽  
Philippe Label ◽  
...  

2018 ◽  
Vol 115 (21) ◽  
pp. 5492-5497 ◽  
Author(s):  
Iskander Said ◽  
Ashley Byrne ◽  
Victoria Serrano ◽  
Charis Cardeno ◽  
Christopher Vollmers ◽  
...  

Chromosomal inversions are widely thought to be favored by natural selection because they suppress recombination between alleles that have higher fitness on the same genetic background or in similar environments. Nonetheless, few selected alleles have been characterized at the molecular level. Gene expression profiling provides a powerful way to identify functionally important variation associated with inversions and suggests candidate phenotypes. However, altered genome structure itself might also impact gene expression by influencing expression profiles of the genes proximal to inversion breakpoint regions or by modifying expression patterns genome-wide due to rearranging large regulatory domains. In natural inversions, genetic differentiation and genome structure are inextricably linked. Here, we characterize differential expression patterns associated with two chromosomal inversions found in natural Drosophila melanogaster populations. To isolate the impacts of genome structure, we engineered synthetic chromosomal inversions on controlled genetic backgrounds with breakpoints that closely match each natural inversion. We find that synthetic inversions have negligible effects on gene expression. Nonetheless, natural inversions have broad-reaching regulatory impacts in cis and trans. Furthermore, we find that differentially expressed genes associated with both natural inversions are enriched for loci associated with immune response to bacterial pathogens. Our results support the idea that inversions in D. melanogaster experience natural selection to maintain associations between functionally related alleles to produce complex phenotypic outcomes.


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