Goats are among the earliest domesticated livestock species, known for their adaptability to diverse climates. Pakistan, with thirty-five indigenous goat breeds and the world’s third-largest goat population, requires genomic characterization to support effective conservation and selection programs. In this study, the data for 827 individuals representing seven Punjab breeds (Beetal, Barbari, Daira Din Panah, Nachi, Pahari, Pothwari, and Teddi) genotyped using the GoatSNP50 Illumina chip were retrieved. After stringent quality control (call rate ≥90%, MAF ≥5%, HWE P<0.0001), 38,890 autosomal SNPs were retained for further analysis. Genetic diversity and relationships among breeds were investigated using principal component analysis (PCA) and linkage disequilibrium (LD) decay profiles with PLINK v1.9.0 and PopLDdecay, respectively. Population structure was evaluated with ADMIXTURE v1.3.0 (K=2–7), selecting the model with the lowest cross-validation error. Allele-based breed-specific markers were identified using a pipeline already established by our group to support breed conservation programs. PCA revealed discrete clustering of breeds based on genetic structure, with Teddi being most distinct breed. Other breeds, including Barbari, Beetal, Daira Din Panah, Nachi, Pahari, and Pothwari, showed partial overlap but remained generally distinguishable. LD decay analysis (using SNP correlation, r², over 100 kb) indicated that Barbari, Daira Din Panah, and Nachi were more uniform as they maintained higher LD at longer distances; however, Teddi and Beetal exhibited faster LD decay, reflecting greater genetic diversity. ADMIXTURE analysis revealed the higher allelic sharing and extensive crossbreeding among breeds, precluding the identification of any breed-specific markers. In conclusion, this study demonstrates genetic stratification and diversity among goat breeds from the Punjab region of Pakistan, but exhibits considerable allelic sharing and gene flow, likely due to crossbreeding. Future studies should target pure-bred animals with higher-density SNP panels or whole-genome resequencing for better understanding of population structure and to validate breed-specific markers.

The yak (Bos grunniens) is not only an animal; it is the biological foundation sustaining life for thousands of pastoral families across the high-altitude Karakoram–Himalayan region of Northern Pakistan (Gilgit-Baltistan and Chitral). At altitudes of up to 4,500 meters, this species and its vital first-generation cross with cattle known locally as Zo or Zomo provide the only reliable sources of milk, meat, fiber, and transport. This system supports a significant population of approximately 25,000 pure yak and over 100,000 crossbreds, representing immense socioeconomic value. However, this critical livestock system is facing a profound genetic crisis. Local herders rely heavily on the Zo/Zomo hybrid for its superior strength and productivity at mid-altitudes (known as hybrid vigor). This practice, while beneficial for immediate production, unintentionally introduces cattle genes into the pure yak population (genetic dilution). This threatens to erase the yak’s unique, millennia-old genetic adaptations to extreme cold and oxygen deprivation, jeopardizing its role as a climate-resilient resource for future generations. To secure this irreplaceable heritage, we propose a strategic overhaul of conservation breeding, driven by population genetics. Our approach is two-fold. a) Genomic Conservation: We will use high-density SNP genotyping to measure the pure yak population's genetic worth with unprecedented precision. The approach permits us to monitor genetic diversity, estimate the effective breeding population size (Ne), and establish secure germplasm repositories to protect its irreplaceable adaptive genes. b) Hybrid Optimization: We will integrate genomic selection into the crossbred population for a systematic improvement in economic performance while strictly controlling and minimizing the harmful influx of cattle DNA into the pure yak genome. By embracing this modern, genomics-based strategy, we aim to maximize the economic benefits of productive hybrids while guaranteeing the long-term genetic integrity and survival of the pure indigenous yak, ensuring the resilience of high-altitude livestock farming against climate change.

Introduction
The increasing global demand for seafood underscores the urgency of developing sustainable and resilient aquaculture systems. The Senegalese sole (Solea senegalensis), a species of high commercial value, plays a pivotal role in enhancing diversification and competitiveness within European aquaculture. However, its benthic nature heightens susceptibility to sediment-associated pathogens, making disease management a persistent production constraint. In alignment with the EU Aquaculture Strategy 2030, which prioritizes environmentally responsible disease mitigation, the BetterFLAT project aims to establish genomic resources to enable the selective breeding of disease-resistant Senegalese sole.

Materials and Methods
The BetterFLAT project employs an integrative multi-omics approach—combining functional genomics, transcriptomics, and molecular marker discovery—to identify genetic determinants associated with resistance to key bacterial pathogens. The consortium, comprising FLATLANTIC, IPMA, and S2AQUA, brings together expertise in aquaculture, pathology, and molecular biology to advance genetic improvement strategies for this species.

Results
An initial pre-test phase optimized pathogen challenge conditions by determining the median (LD₅₀) and 75% (LD₇₅) lethal doses for selected bacterial isolates. Experimental fish were subjected to a range of bacterial concentrations, and cumulative mortality was recorded to assess isolate virulence. Molecular characterization, including species confirmation and virulence gene profiling, validated the selection of the most pathogenic and genetically defined strain for subsequent infection trials.

Discussion and Conclusion
Through the integration of multi-omics datasets with pathogen-challenge experiments, the BetterFLAT project lays the groundwork for the development of disease-resilient Senegalese sole broodstock. These advances are expected to enhance juvenile robustness, reduce production losses, and promote more sustainable and economically viable aquaculture practices.

Acknowledgments
The operation BetterFLAT was developed with funding from Programmes COMPETE2030, Algarve2030, Portugal2030, and the European Union; the Interface Mission cofinanced by PRR - Plano de Recuperação e Resiliência by the European Union (operation code 01/C05-i02/2022.P148); and SAUDE&AQUA II (MAR-021.1.3-FEAMPA-00018).

Climate change poses increasing challenges to livestock productivity and health, particularly in tropical and subtropical regions. Genomic technologies have emerged as powerful tools to enhance both disease resistance and environmental adaptability in animals. Several studies have demonstrated that integrating genomic selection, genome-wide association studies (GWAS), and functional genomics can accelerate breeding for resilience traits (Boettcher et al., 2015; Knap & Doeschl-Wilson, 2020). This review synthesizes evidence from seven recent studies addressing genomic adaptation and disease resistance in livestock species, including cattle, sheep, goats, and pigs. The selected works applied methodologies such as GWAS, SNP mapping, transcriptomic profiling, and selection signature analysis (Boettcher et al., 2015; Genomic Responses to Climatic Challenges in Beef Cattle, 2024; BMC Genomics, 2024; Genome Biol. Evol., 2020). These approaches were evaluated in the context of climate-related stressors such as heat tolerance, pathogen pressure, and environmental variability. Across species, genomic regions associated with heat stress tolerance and immune response have been consistently identified. For instance, heat-adapted cattle populations show selection signatures in genes such as TRPM8, HSP70, and SOD2 (Genomic Responses to Climatic Challenges in Beef Cattle, 2024). In goats, climate adaptation was linked to immune-related loci detected through landscape genomics (BMC Genomics, 2024). Likewise, studies in pigs and sheep revealed that resilience to polymicrobial diseases and weather variation is heritable and can be enhanced through genomic selection (Knap & Doeschl-Wilson, 2020; BMC Genom. Data, 2020). Collectively, these findings emphasize that genomic tools can identify adaptive variants and accelerate breeding for combined resilience to disease and climate stress. Genomic-based breeding therefore represents a sustainable strategy to improve livestock productivity and welfare under global climate change. Future directions should include the integration of multi-omics datasets and large-scale genomic databases to strengthen precision livestock adaptation strategies.

Introduction

Growth variability in gilthead seabream (Sparus aurata) remains a key challenge for Mediterranean aquaculture, as fish reared under identical conditions often show large differences in growth rate, which has an economic impact on fish farmers. The molecular basis of this variability is still unclear, as most studies thus far have focused on the targeted gene expression analysis of a limited set of genes.

Methods

A trial conducted at EPPO/IPMA investigated the molecular mechanisms behind fish growth disparities. Sparus aurata showing growth differences were classified into slow- and fast-growing groups based on average batch weight, maintaining equal density across tanks. Muscle samples from six fish per group were analyzed using RNA-seq for differential gene expression (DGE).

Results

Fast-growing fish exhibited superior growth and physiological performance. A total of 1,190 genes were differentially expressed between groups, with 524 up-regulated and 666 down-regulated in fast growers. The most up-regulated genes—tmprss9, ctxn3, nlrp12, dpy30, and znf608—were linked to muscle development, cytoskeletal organization, and transcriptional regulation. Among the most down-regulated were mfap4, dhys, and mdn1, primarily involved in immune response, extracellular matrix remodeling, and energy-demanding processes.

Conclusion

These results reveal distinct molecular signatures associated with growth capacity in seabream. The use of RNA-seq on muscle tissue proved to be effective for identifying genes and regulatory networks directly related to growth performance. The identified set of genes offers potential biomarkers for predicting growth rate, thereby improving aquaculture management. This research advances understanding of growth variability in S. aurata, providing a foundation for strategies to enhance production efficiency, such as selective breeding programs.

Acknowledgments

This study was funded by NanoPEIXE (ALG-01-0247-FEDER-070032), INOVAQUA (MAR-021.1.3-FEAMPA-00004), and Interface Mission cofinanced by PRR (Plano de Recuperação e Resiliência), European Union (operation code 01/C05-i02/2022.P148).

Carnivores represent important ecological components as apex predators, but their diversity is still poorly described in Saudi Arabia due to a deficiency of field data. This study provides the first molecular assessment of carnivores across southern Saudi Arabia using a multilocus DNA barcoding approach (COI, Cytb, and 16S). Out of 155 biological samples (scats and tissues), we successfully generated and analyzed 152 sequences, identifying 11 species (Panthera pardus, Caracal caracal, Acinonyx jubatus, Felis lybica, Vulpes vulpes, Canis lupus, Canis lupus familiaris, Hyaena hyaena, Genetta genetta, Ichneumia albicauda, and Herpetes javanicus). Phylogenetic and haplotype network analyses uncovered clear resolution at the species level with substantial intraspecific variation, especially within Vulpes vulpes, Canis lupus, and Panthera pardus. We have also confirmed, for the first time since the sighting in 2014, the presence of the critically endangered Arabian leopard, Panthera p. nimr. The observed high genetic diversity among the studied leopard samples likely reflects the temporal divergence of the sampled specimens rather than the true current population diversity. The cheetah (Acinonyx jubatus) samples in our study likely represent introduced individuals from Africa via illegal trade, rather than native Arabian populations. Genetic divergence among haplotypes reveals historical isolation and recent population expansions favored by habitat fragmentation. The proposed methodology of integrating molecular barcoding with traditional field approaches may hold great potential for the protection of the elusive and threatened carnivore fauna of Saudi Arabia.

The Latvian Dark-head (Latvijas tumšgalve; LT) is the sole species developed in Latvia, having fully acclimatised to the local climatic circumstances. It is the only national breed, possessing cultural importance and contributing to traditional lifestyles, landscape conservation, and regional identity. As commercially desirable sheep breeds prevail, indigenous genetic resources, especially in small agricultural communities, are at heightened risk of extinction.

This study assesses the genetic diversity of the LT breed and compares it with other prevalent sheep breeds in Latvia. For the first time, lambs from sire rams of prominent breeds in Latvia were genotyped using the Illumina Ovine SNP50 BeadChip®. The analysis of genetic diversity encompassed evaluations of minor allele frequency (MAF), and distinct breed markers were identified by ascertaining fixed SNPs (MAF = 0) that are exclusive to each breed.

This research identified 27,561 highly polymorphic SNPs (MAF 0.3–0.5) in LT breed samples, demonstrating considerable genetic differences from other breeds. Of the identified SNPs, 2,668 (5.45%) were fixed in the LT breed, with 55 to 131 SNPs being exclusive to it in comparison to other breeds. The OvineSNP50 panel is a crucial tool for elucidating the genetic architecture of the LT breed, facilitating the identification of unique genetic characteristics and differences from other breeds.

The results provide an additional understanding of the genetic background of the Latvian national sheep breed, creating new opportunities for genetic research and the development of genetic selection in the Latvian sheep population.

Acknowledgements: This study received support from the Latvian Council of Science, specifically through projects LZP-2021/1-0489 and LZP-2024/1-0092.

​This four-year study, conducted from April 2013 to May 2017, provides a comprehensive inventory and update on the geographical distribution of wild carnivorous mammals in Western Algeria, with a specific focus on regionally endangered species. Spanning diverse biotopes, the primary objective was to establish a robust baseline assessment of the local carnivore population status.

​The investigative work employed a multi-source methodology, combining extensive direct and indirect observation (tracks, scat, and sightings) with surveys and questionnaires conducted among local communities, hunters, and forestry agents. This approach allowed for the collection of current ecological data alongside historical records across the study area.

​The research successfully documented 14 carnivorous mammal species across six families. Canids (Canis aureus, C. lupus, Vulpes rupellii, V. vulpes) were widely distributed. In contrast, Felids—including the regionally threatened Felis libyca, F. margarita, and F. caracal—were poorly represented. Mustelids (five species, including Lutra lutra) showed restricted distributions, and Hyaenidae (Hyaena hyaena) presence was minimal. Both the Viverrid (Genetta genetta) and Herpestidae (Herpestes ichneumon) were observed in low numbers, indicating a significant risk of extinction.

​These findings confirm the persistently endangered conservation status of these carnivore guilds, necessitating immediate intervention. The comprehensive data, including biological samples for genetic analysis, emphasizes the need for national and international cooperation to manage this valuable genetic material. This work also strongly complements the magnificent conservation efforts underway for the Saharan Cheetah (Acinonyx jubatus hecki), providing vital, up-to-date information for developing targeted protection strategies in Western Algeria.

The koala (Phascolarctos cinereus), an iconic Australian marsupial, continues to experience severe population declines due to habitat loss, disease, and climate change, and is now listed as Endangered across eastern Australia. Effective conservation of koalas requires a standardised genomic tool to ensure data is directly comparable over time and space, strengthening conservation efforts. We therefore developed an integrated single nucleotide polymorphism (SNP) genotyping assay, incorporating ~5,000 informative loci derived from published genomic datasets, and novel SNPs identified from candidate fitness-related genes and major koala pathogen genomes/genes. This unified assay incorporates both host and pathogen markers, enabling comprehensive genomic monitoring through a single, streamlined workflow. The assay, which was validated using over 1,000 koalas collected across the species’ distribution, demonstrated high genotyping success and reproducibility across sample types including blood, tissue, urogenital swabs, hair, scat, and archived DNA. It supports multiple applications such as assessing population structure and connectivity, provenance, relatedness estimation, sex determination, and screening for pathogens including koala retrovirus and papillomavirus. The assay provides a robust, cost-effective framework for both fine- and broad-scale management by standardising data generation and comparison across studies and regions. By integrating host and pathogen genomics, this multi-purpose approach improves understanding of koala biology and strengthens evidence-based decision-making in conservation programs. The platform establishes a scalable model for wildlife genomics, enabling efficient, evidence-based management of threatened species.

Introduction:
Honey bees play a critical role in pollination and the maintenance of biodiversity. In Algeria, bee populations face multiple health challenges due to apicultural diseases, including viral, bacterial, and parasitic infections, as well as infestations by Varroa destructor. These pathologies threaten colony survival, reduce honey production, and may negatively affect agricultural ecosystems. The aim of this study is to assess the prevalence and regional distribution of major honey bee diseases in Algeria to inform targeted prevention and management strategies.

Methods:
A national survey was conducted between 2023 and 2024, covering 15 apiaries across different climatic and ecological zones of Algeria. Colony samples were collected and analyzed for bacterial infections (Paenibacillus larvae), viral diseases (e.g., Deformed Wing Virus), and parasitic infestations, including Varroa destructor and Nosema spp. Data were analyzed to determine disease prevalence, regional patterns, and risk factors associated with environmental and management conditions.

Results:
The study revealed a high prevalence of key apicultural diseases, with notable variations between regions. Varroa destructor emerged as the most widespread parasite, followed by bacterial and viral infections. Apiaries located in intensive agricultural areas exhibited higher disease incidence, suggesting a link between agricultural practices and colony health. Seasonal and environmental factors also influenced disease prevalence, highlighting the need for context-specific management approaches.

Conclusion:
These findings underscore the importance of regular monitoring and integrated disease management in Algeria. Strengthening preventive measures, raising awareness among beekeepers, and promoting sustainable apicultural practices are essential to safeguard honey bee health, ensure colony productivity, and support biodiversity conservation. This study provides a foundation for developing effective strategies to mitigate the impact of apicultural diseases in the region.