Genetic Programming Research Articles

Outcomes of the premarital screening program in Riyadh Region, KSA in 2021–2022: A cross-sectional study

ObjectiveThis study investigated the prevalence of sickle cell disease, β-thalassemia, human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV) and their demographic associations in Riyadh, KSA. MethodA retrospective cross-sectional design was used for this study. National data were obtained from The Healthy Marriage Program for the Riyadh region. Variables involved in the data collection tool were demographic data, lab results for hematology and serology tests and diagnosis, and the status of the certificate. A single sample K–S test was used to determine the normality of the data. We used the multiple logistic regression model. The odds ratio (OR) with 95% confidence interval (CI) were reported for both bivariate and multivariable analyses. P < 0.05 was considered statistically significant. ResultThe study screened a total of 916,295 participants, comprising 452,474 in 2021 and 463,821 in 2022. The sex distribution was 51.7% male and 48.3% female, with a mean age (± standard deviation) of 43 (±11.8) in 2021 and 41 (±11.9) in 2022. Among the participants, there were 196 sickle cell disease (SCD) cases and 4610 carriers. Additionally, 1069 participants tested positive for infectious diseases. Sex was a notable factor in SCD, HIV, HBV, and HCV cases. ConclusionOur findings highlight the importance of ongoing surveillance and intervention efforts through programs such as premarital screening and genetic counseling programs. These initiatives are crucial for identifying at-risk individuals and reducing the burden of genetic disorders and infectious diseases with targeted public health strategies. Future research should focus on longitudinal studies to monitor trends and assess the long-term impact of preventive measures on disease prevalence and distribution in the region.

Research on porosity prediction method for petroleum reservoirs based on improved gene expression algorithm

Abstract Porosity, an essential parameter of reservoir properties, plays a crucial role in reservoir evaluation. Indirect prediction of reservoir porosity using well-logging data is a fundamental task in assessing hydrocarbon reserves. Multivariate stepwise regression and artificial neural network methods are currently typical prediction approaches. However, these methods suffer from drawbacks such as high workload, extensive training sample requirements, and high computational costs. Genetic Expression Programming (GEP), a novel genetic algorithm, exhibits remarkable function discovery capabilities, high efficiency, and the ability to function without requiring large training samples. This paper proposes a method that utilizes GEP to mine a porosity calculation model from well-logging sample data and subsequently compute the porosity. The effectiveness and efficiency of this method are validated through actual well-logging data.

Genomic Correlation, Shared Loci, and Causal Relationship Between Bullous Pemphigoid and Atopic Dermatitis: A Large-Scale Genome-Wide Cross-Trait Analysis.

Bullous pemphigoid (BP) and atopic dermatitis (AD) are currently thought to be tightly related, yet studies of the mechanisms of co-morbidities are lacking. We obtained GWAS data for BP (N = 376,274) and AD (N = 796,661) from the Finnish Genetic Research Program dataset and the UK Biobank, separately. Then, the following four analyses were performed: (1) cross-trait linkage disequilibrium score regression (LDSC) to assess the genetic correlation between BP and AD, (2) cross-phenotype association analysis (CPASSOC) to identify multiple effector loci shared by BP and AD, (3) transcriptome-wide association study (TWAS) to determine whether their cross-organizational expression patterns share genes with a common biological mechanism of relevance, and (4) bidirectional Mendelian randomization (MR) analysis to assess bidirectional causal effects of BP and AD. We found a positive genetic association between BP and AD (rg = 0.5476, p = 0.0495) as well as identified four pleiotropic loci and 59 common genes affecting BP and AD. Bidirectional MR analysis suggested that BP promotes the risk of AD. We revealed a genetic link between BP and AD, which is associated with biological pleiotropy and causality. Awareness of the association between BP and AD helps dermatologists manage patients with these illnesses.

Freezability of Semen Collected from Ganders of 12 Breeds Covered by the Polish Genetic Resources Conservation Program

Abstract A rapid decline in wild animal biodiversity, as well as in the number of local livestock breeds of lower economical values, makes species and breeds protection and creation of genetic reserves a necessity and a challenge of the 21st century. For birds, semen freezing is still the best method of gene preservation ex situ in vitro. The aim of the presented study was to assess the susceptibility to freezing process and to establish the semen gene bank of twelve goose breeds covered by the Polish genetic resources conservation program. Sexually mature ganders were randomly selected from four northern local breeds: Kartuska, Pomorska, Rypinska, Suwalska, four southern local breeds: Garbonosa, Kielecka, Lubelska, Podkarpacka, and four foreign goose breeds: Kuban, Landes, Roman and Slovakian. Each breed was represented by 12 males, twelve repetitions were carried out. Semen samples were frozen in a computer-controlled cryogenic chamber using a method developed for White Koluda goose. The basic evaluation criterion was sperm morphology in fresh and freeze-thawed semen assessed in nigrosine-eosin stained histological smears. The percentage of live in total and live normal sperm in the fresh semen differed significantly (P&lt;0.05) between breeds. Semen of Kartuska and Suwalska ganders (northern breeds), contained the highest percent of live sperm – 94.4 and 94.1 respectively, including 52.5% and 54.2% of live normal sperm, while the lowest number of these forms was observed for Slovakian goose – 86.4% and 29.2%, respectively. The freezing process resulted in a significant (P&lt;0.05) reduction in the total number of live and live normal sperm and an increase in dead sperm in all groups. Cryopreservation process was the most effective in case of Suwalska goose semen (28.4% of live normal cells in thawed semen) and the less profitable for Landes (7.4% of live normal cells). The analyses showed significant differences between breeds in sperm morphology in fresh and thawed semen. Moreover, the high proportion of live spermatozoa in the fresh semen did not guarantee a high proportion of spermatozoa after thawing, indicating the differences in semen susceptibility to cryopreservation process depending on goose breed.

Data-driven bio-integrated design method encoded by biocomputational real-time feedback loop and deep semi-supervised learning (DSSL)

Today, under the imperatives of synthetic biology (Synbio), material-based design strategies are conceived as biofactories that can recapitulate the functionalities of living systems for developing building materials with controllable structural features. These strategies include biofabrication techniques such as vitro-culturing, Fabrication Information Modeling (FIM), growth parametrization, machinery systems, and genetic programming articulated bioproducts as the construction material for low-carbon buildings. However, these biophysical systems need interactive development by data-oriented models and decision-maker tools that can mine, measure, and re-configure the complexity in biological systems through monitoring and controlling in a higher integration toward systemic decision-making solutions. This research presents a real-time feedback loop as the bio-integrated design method for design and fabrication of Gluconacebacter Xylinus (GX) Bacterial Cellulose (BC) with Transfer Learning (TL) and Deep Semi-Supervised Learning (DSSL) through TensorFlow and Keras Python libraries. The loop started by mining datasets from BC growth via the VGG16 pre-trained model. In this stage, the loop can learn the material behavior over the growth process and attribute features to a measured BC thickness. Based on this attribution, the loop can drive real-time classifying of input datasets to thickness-based classes and guide the Region of Interests (ROIs) to a user-designed thickness till the captured features are fitted to the user-input class features. The training results over 8640 images show a 0.001 learning rate, an average loss of 0.18 (540 total steps), an accuracy of 0.706, and a precision of 0.752 for the feature extractor model. For the classifier, a 0.15 average loss (3375 total steps), an accuracy of 0.829, and a precision of 0.712 demonstrate the models' efficiency in pattern recognition and classification. Also, the loop operation persistently exhibits a more than 50% precision rate, displaying the loop's high performance in achieving user-designed 3D shapes. This research aims to a transformative shift in bio-integrated design based on feedback loops as the foundational step towards intelligent bio-digital design platforms. Also, this ground can break designing with biological systems based on desired tasks for the new generation of designers called biodesigners.

Control of sporophyte secondary cell wall development in Marchantia by a Class II KNOX gene.

Land plants evolved from an ancestral alga around 470 mya, evolving complex multicellularity in both haploid gametophyte and diploid sporophyte generations. The evolution of water-conducting tissues in the sporophyte generation was crucial for the success of land plants, paving the way for the colonization of a variety of terrestrial habitats. Class II KNOX (KNOX2) genes are major regulators of secondary cell wall formation and seed mucilage (pectin) deposition in flowering plants. Here, we show that, in the liverwort Marchantia polymorpha, loss-of-function alleles of the KNOX2 ortholog, MpKNOX2, or its dimerization partner, MpBELL1, have defects in capsule wall secondary cell wall and spore pectin biosynthesis. Both genes are expressed in the gametophytic calyptra surrounding the sporophyte and exert maternal effects, suggesting intergenerational regulation from the maternal gametophyte to the sporophytic embryo. These findings also suggest the presence of a secondary wall genetic program in the non-vascular liverwort capsule wall, with attributes of secondary walls in vascular tissues.

Flexible Job Shop Composite Dispatching Rule Mining Approach Based on an Improved Genetic Programming Algorithm

Flexible Job Shop Composite Dispatching Rule Mining Approach Based on an Improved Genetic Programming Algorithm

Modular Multitree Genetic Programming for Evolutionary Feature Construction for Regression

Modular Multitree Genetic Programming for Evolutionary Feature Construction for Regression

Exploring barriers to completing referral appointments for cancer genetic services in a rural state.

83 Background: Genetic counseling and testing promotes awareness and management of hereditary cancer risk. Barriers exist to accessing cancer genetic services, particularly among those with healthcare disparities, i.e., those facing geographic and socioeconomic barriers. These barriers impact not only the ability to obtain a referral but also whether the initial appointment is scheduled and completed. This study explored referrals and what factors were associated with whether appointments were successfully completed in a predominantly rural state (Maine). Methods: Medical records were reviewed for patients referred to the state’s largest health system-based cancer genetic program from 2017 through 2023. We evaluated factors that may be associated with referral completion within 90 days. These included: year of referral, patient factors, clinical factors, and health system factors. Associations were examined using univariate logistic regression models. Results: A total of 11,643 referrals were placed and examined over the period studied. Despite a steady increase in the number of referrals, the percent of referrals that were successfully completed decreased over time (54.04% in 2017 to 51.06% in 2023). Patients with older age and whose primary language was identified as English had greater likelihood of completing the referral (OR = 1.01; p &lt; 0.001 and OR = 3.37; p &lt; 0.001, respectively). Patients living in isolated rural areas and those without insurance were less likely to complete the referral (OR =0.84 and OR 0.61; p &lt; 0.001, respectively). Patients with a cancer diagnosis were almost three times more likely to complete the referral (OR = 2.93; p &lt; 0.001). Referrals scheduled as telemedicine appointments were less likely to be completed (OR =0.63; p &lt; 0.001); and referrals coming from providers within the health system were twice as likely to be completed (OR = 2.15; p &lt; 0.001). Conclusions: Successful completion of referral appointments to cancer genetic services varied by several important patient, clinical, and health system factors. Further multivariate analyses will be conducted. Strategies including language translation, educational materials, and financial assistance might boost the completion rate for structurally vulnerable patients. Systems aimed at streamlining the scheduling process are needed to support all individuals in accessing cancer genetic services, with a focus on those with healthcare disparities.

Improved access to genetics for individuals with potential germline mutations identified on somatic testing.

339 Background: Somatic testing is increasingly common in treating cancer and may identify mutations that necessitate confirmatory germline genetic testing. Management of these results varies by institution. From 2021-2024, we completed an iterative approach to determine the most effective method for follow-up germline testing. Methods: We conducted 3 six-month sequential phases to determine the most effective approach to follow up on somatic findings concerning for germline origin. Phase I (3-9/2021), consisted of weekly e-mail notifications sent by the genetics program to the referring provider regarding patients who had somatic mutations of potential germline origin, and recommended providers refer the patient to genetics. Phase 2 (10/2021-4/2022), consisted of monthly e-mail notifications to the referring provider, clinical staff and included cancer center leadership. In phase 3 (10/2023-4/2024), GC assistants and medical secretaries facilitated referrals and direct outreach to schedule patients for germline follow-up. We measured the percentage of patients referred to genetics, who completed germline testing, and had confirmed pathogenic germline mutations. Results: In Phase I, 38% of patients were referred to genetics, 23.5% completed germline testing, and 37% had positive results (Table 1). In Phase 2, 19% of patients were referred to genetics, 4.7% completed germline testing, and 43% had positive results. In Phase 3, using the GC facilitated approach, 87.5% (70/80) of patients were referred. Those not referred had already undergone germline testing, were deceased or transferred care out of state. Of the 70 patients, 38 met with a GC and 30 elected to proceed with germline testing. There are 25 (36%) genetic test results available to date. 37% (26/70) patients did not complete a genetics appointment. 58% (15/26) could not be reached to schedule an appointment. Nine individuals declined or deferred an appointment. Five patients were deceased before a genetics appointment could be coordinated. For those that received referrals to genetics in phase 3, the germline positive results rate was 92% (23/25). Conclusions: The GC driven referral pathway was most effective at facilitating referral and completion of confirmatory testing for patients with somatic findings concerning for germline origin. Follow-up of these results shows an extremely high rate of germline positive results, making subsequent testing imperative for centers treating cancer patients. Given implications for cascade testing, future research is needed to study upfront consenting approaches to automate subsequent germline testing and notification in this population. Phase Intervention Potential Germline n, (%) Referred n , (%) Completed n , (%) Germline Positive n , (%) 1 Weekly Emails 162 62 (38%) 38 (61%) 14 (37%) 2 Monthly Emails 150 28 (19%) 7 (25%) 3 (43%) 3 GC Driven Referrals 80 70 (87.5%) 25 (36%) 23 (92%)

A novel bi-level decision-making approach based on game theory for mechanism design

This study addresses the bi-level multi-objective optimization problems raised in reliability-based robust design optimization (RBRDO) of engineering applications through establishing a state-of-the-art game theoretic scenario. A novel bi-level decentralized decision-making approach is proposed using the synergy of RBRDO, game theory, Monte Carlo simulation (MCS), and genetic programming (GP). The application of the proposed approach is elaborated in a case study of robust synthesis of high-speed path-generating four-bar mechanisms. The four performance criteria, namely, accuracy ( TE), robustness ([Formula: see text] TE and [Formula: see text]2 TE), reliability ( f G) at the upper level, and quality of motion ( TA) at the lower level are assigned to four players so that each of whom is in charge of one objective criterion. The peak input driving torque ( T S) is associated with the upper-level problem. The GP meta-model is used to capture the Stackelberg protocol that is, constructing the follower’s rational reaction set (RRS) and the Nash bargaining function is hired to model the cooperative behavior. The obtained results show a considerable enhancement in reliability and robust behavior of mechanism, while the deterministic criteria of accuracy and quality of motion are preserved.

Marker Assisted Selection (MAS) and It's Application in Vegetable Crop Improvement

Vegetable crop breeding has changed dramatically since the early 1980s due to technological breakthroughs, especially high-throughput sequencing and molecular marker technologies, which have made it possible to sequence many plant genomes, create dense genetic maps, and identify important genes and QTLs linked to traits like yield and disease resistance. ..These instruments have expedited genetic research and breeding programs in crops including tomato, pepper, eggplant, and cucumber, establishing marker-assisted selection (MAS) as a crucial component of contemporary breeding. The use of these technologies has improved crop characteristics significantly and is still influencing the development of vegetable crops in the future. .. For instance, in the majority of private and public tomato breeding projects, major-gene disease resistance traits like verticillium wilt and anthracnose are selected for using PCR-based markers such as SCAR and CAPS.Bs5 and Bs6 have broad-spectrum resistance against Xanthomonas spp. against chilli leaf spot thanks to marker-assisted gene pyramiding. Major QTLs associated to SSR marker CAMS451 on chromosome 1 (from Capsicum accession LS2341) and marker ID10-194305124 on chromosome 10 (from C. annuum BVRC1) have been mapped for resistance to Ralstonia bacterial wilt.Constantly searching crop germplasm for new resistance genes or alleles is essential to diversify the gene pool and stop resistance from breaking down. By using marker-assisted selection (MAS), it is possible to combine genes for resistance to different pathogens or several sources of resistance to the same pathogen to create novel cultivars.

Merinos in Poland – an analysis of breeding condition, selected performance traits and perspectives for the protection of genetic resources in relation to the country’s total sheep population

The purpose of the study was to analyse the breeding condition and performance traits of merino sheep belonging to three breeds in 2008-2022. The experimental material consisted of data derived from annual reports published by the Polish Sheep Breeding Association on breeding of three merino breeds: Polish Merino, Coloured Merino, old-type Polish Merino and data on the number and distribution of flocks, as well as data on the implementation of the sheep genetic resources protection programme from the database of the National Research Institute of Animal Production covering the period of the last 15 years. Analysing the population size over the last 15 years, significant changes were observed in the breed structure of the Merino sheep population. The implementation of conservation programmes and the opportunity to obtain subsidies for conservation breeds have had an impact on the breeding of these breeds in our country. Currently, the largest share of the merino sheep population is represented by the old-type Polish merino. Merino breeding has a regional and large-scale profile, concentrated in the historical areas of their maintenance, in Wielkopolska and Kujawy, usually in flocks of about 100 dams. Reproduction rates expressed by maternal prolificacy were found to be in line with the breed pattern. The Polish merino and the old-type Polish merino were distinguished by similar parameters of reproductive traits and higher fertility as well as rearing indices than those of the coloured merino. The coloured merino is the breed with the highest fertility and breeding performance. Body weight of lambs was higher for the white varieties. However, reproductive and meat performance indices show the potential of merino sheep in the context of lamb production, which is currently the main focus of sheep production in Poland.

“I Didn't Have to Worry about It”: Patient and Family Experiences with Health System Involvement in Notifying Relatives of Genetic Test Results

Introduction: In the USA, patients who undergo genetic testing for hereditary cancer risk are responsible for informing relatives about their genetic test results, but many relatives never find out they might be at risk. A health system-mediated relative notification program might help fill this gap, but questions remain about the acceptability of this approach. Methods: We analyzed qualitative data from a single-arm, nonrandomized, mixed-methods study to understand how patients and families experienced a new health system-mediated relative notification program. We invited all study participants to participate in semi-structured telephone interviews at 6–8 weeks after return of genetic test results. We used a template analysis approach to thematically analyze interview transcripts. Results: We interviewed 32 participants, including 17 probands and 15 relatives. Relatives reported positive experiences with the notification program, noting they felt in control of decisions and appreciated genetic counselor involvement in communicating the proband’s test results. Benefits of direct contact included reduced burden for probands, increased family discussions about health, and notification of relatives who otherwise would not have learned results. No participants reported adverse effects from the program. Conclusion: Overall, the relative notification program was acceptable to participants and supported probands in reaching at-risk relatives who otherwise might not have been notified. These findings could inform the implementation of future genetic risk family notification programs with the potential to improve uptake of cascade testing and advance cancer prevention and early detection efforts.

A Linear Genetic Programming Approach for the Internet Shopping Optimization Problem with Multiple Item Units (ISHOP-U)

A Linear Genetic Programming Approach for the Internet Shopping Optimization Problem with Multiple Item Units (ISHOP-U)

Effects of Ethylene Inhibitors on the Long-Term Maintenance of the Embryogenic Callus of Vitis vinifera L.

Vitis vinifera is an important fruit crop which is mainly consumed fresh or used for the production of wine. Genetic improvement programs through New Genomic Techniques (NGTs) aim to develop grapevine varieties resistant to biotic and abiotic stresses or enhancing nutraceutical properties. In order to apply NGTs, maintaining embryogenic calluses from flower tissues is critical. Optimizing culture conditions—pH, gelling agents, temperature, light, growth regulators, and gas composition—is essential for inducing efficient embryogenic responses tailored to each genotype/explant. Ethylene, a pivotal gaseous plant hormone, significantly influences tissue culture by affecting organogenesis and embryogenesis processes in several plants. Modulating ethylene levels shows promise for improving tissue culture vitality. This study evaluates in Vitis vinifera the effects of silver thiosulfate (STS) and salicylic acid (SA) on embryogenic callus growth, specifically investigating their roles in maintaining and inducing embryogenic competence. STS, particularly at 40 µM and 60 µM concentrations, effectively preserved embryogenic competence in Italia and Red Globe calluses, while high SA concentrations showed varied and occasionally adverse effects. At the same time, STS markedly suppressed the non-embryogenic callus growth in recalcitrant variety Italia, potentially increasing the ratio between embryogenic to non-embryogenic calluses development.

Dynamical Sphere Regrouping Particle Swarm Optimization Programming: An Automatic Programming Algorithm Avoiding Premature Convergence

Symbolic regression plays a crucial role in machine learning and data science by allowing the extraction of meaningful mathematical models directly from data without imposing a specific structure. This level of adaptability is especially beneficial in scientific and engineering fields, where comprehending and articulating the underlying data relationships is just as important as making accurate predictions. Genetic Programming (GP) has been extensively utilized for symbolic regression and has demonstrated remarkable success in diverse domains. However, GP’s heavy reliance on evolutionary mechanisms makes it computationally intensive and challenging to handle. On the other hand, Particle Swarm Optimization (PSO) has demonstrated remarkable performance in numerical optimization with parallelism, simplicity, and rapid convergence. These attributes position PSO as a compelling option for Automatic Programming (AP), which focuses on the automatic generation of programs or mathematical models. Particle Swarm Programming (PSP) has emerged as an alternative to Genetic Programming (GP), with a specific emphasis on harnessing the efficiency of PSO for symbolic regression. However, PSP remains unsolved due to the high-dimensional search spaces and local optimal regions in AP, where traditional PSO can encounter issues such as premature convergence and stagnation. To tackle these challenges, we introduce Dynamical Sphere Regrouping PSO Programming (DSRegPSOP), an innovative PSP implementation that integrates DSRegPSO’s dynamical sphere regrouping and momentum conservation mechanisms. DSRegPSOP is specifically developed to deal with large-scale, high-dimensional search spaces featuring numerous local optima, thus proving effective behavior for symbolic regression tasks. We assess DSRegPSOP by generating 10 mathematical expressions for mapping points from functions with varying complexity, including noise in position and cost evaluation. Moreover, we also evaluate its performance using real-world datasets. Our results show that DSRegPSOP effectively addresses the shortcomings of PSO in PSP by producing mathematical models entirely generated by AP that achieve accuracy similar to other machine learning algorithms optimized for regression tasks involving numerical structures. Additionally, DSRegPSOP combines the benefits of symbolic regression with the efficiency of PSO.

Real-time prediction of river ice breakup phenomena: A jittered genetic programming model and wavelet analysis integrating remotely sensed imagery and machine learning

Forecasting the timing of breakup ice jams in rivers is crucial for early flood warning and effective management in cold regions where rising river flows can lead to significant damage. However, this task is hindered by insufficient data and the complex dynamics of river ice. These obstacles pose challenges in developing precise forecasting models. This study aimed to address the data scarcity issue by introducing innovative machine learning methods, focusing on classification and jittering (J), binary genetic programming (BGP), and wavelet transform (WT) for river ice forecasting (WT-JBGP) in the Tornio River, situated between Finland and Sweden. By considering time scales ranging from 2 to 32 days and time lags of 1 to 3 days, this method was applied to enhance the predictive capabilities of predictors. The findings reveal that certain predictors, with specific time scales and time lags, significantly influence the timing of breakup events. These include the 8-day temperature and 32-day discharge, both with a 2-day lag time, as well as the 4-day precipitation, approximation of albedo, and 16-day atmospheric pressure at ground level, all with a 1-day lag obtained from ERA5 and recorded data. Additionally, we conducted a quantitative evaluation of the effectiveness of the proposed model and contrasted its efficacy with that of BGP, WT-BGP, and advanced J-BGP techniques. The WT-JBGP model attains the highest overall classification accuracy of approximately 0.91, alongside a Heidke Skill Score exceeding 0.78, and a Positive Predictive Value surpassing 0.85, thereby demonstrating its superiority over competing methodologies. In summation, this study offers a promising approach to overcoming observed data scarcity in breakup date prediction, providing valuable insights into river ice dynamics.

A review of porcine skeletal muscle plasticity and implications for genetic improvement of carcass and meat quality*

Skeletal muscle is characterized by a remarkable plasticity to adapt to stimuli such as contractile activity, loading conditions, substrate supply or environmental factors. The existing knowledge of muscle plasticity along with developed genetic and genomic technologies, have enabled creating animal breeding strategies and allowed for implementing agriculturally successful porcine genetic improvement programs. The primary focus of this review paper is on pig skeletal muscle plasticity as it relates to genetic improvement of desirable carcass composition and pork quality traits. Biological constraints between practically realized breeding objectives, pig skeletal muscle biology, and pork quality are also discussed. Future applications of genetic and genomic technologies and plausible focus on new breeding objectives enhancing pork production sustainability are proposed as well.

Knockout of rbm24a and rbm24b genes in zebrafish impairs skeletal and cardiac muscle integrity and function during development.

Skeletal and cardiac muscles are contractile tissues whose development and function are dependent on genetic programs that must be precisely orchestrated in time and space. In addition to transcription factors, RNA-binding proteins tightly regulate gene expression by controlling the fate of RNA transcripts, thus specific proteins levels within the cell. Rbm24 has been identified as a key player of myogenesis and cardiomyogenesis in several vertebrates, by controlling various aspects of post-transcriptional regulation, including pre-mRNA alternative splicing and mRNA stabilization. In zebrafish, knockdown of rbm24a or rbm24b also causes skeletal and cardiac muscle phenotypes, but how their combined loss affects muscle integrity and function remains elusive. By genome editing, we have generated rbm24a and rbm24b single mutants as well as double mutants. Structural analyses indicate that homozygous rbm24a and rbm24b double mutants exhibit severe somitic muscle and cardiac phenotypes, although rbm24b single mutants are obviously normal. We further show that the loss of rbm24a and rbm24b disrupts sarcomere organization, impairing functional contractility and motility of skeletal and cardiac muscles. The rbm24 mutant zebrafish represents a new genetic tool for in-depth studies of Rbm24-mediated post-transcriptional regulation of skeletal and cardiac muscle development, disease and regeneration.