Abstract Background and aims Common bean ( Phaseolus vulgaris L.) is an important food legume which contributes to sustainable agriculture by fixing atmospheric nitrogen (N). However, modern breeding programs have mostly focused on improving crop yield and agronomic traits, ignoring the crop’s capacity for effective symbiotic nitrogen fixation and interactions with microbial communities. We sought to investigate how genotype, soil N availability, and environmental conditions, affect plant growth, N fixation, and the composition of root-associated bacterial communities of 16 bean cultivars released over 77 years of breeding history. Methods Crop growth parameters of 14 pintos, 1 pink, and a non-nodulating navy bean R99 were evaluated in field trials conducted over two growing seasons under differing N soil fertility. The soil and root microbiomes associated with these cultivars were analyzed using 16S rRNA amplicon sequencing. Results The results revealed significant year-to-year differences in crop yield and SNF. While nodulation rates were consistent, N fixation efficiency declined under high soil N conditions. Cultivar-specific differences in microbiome composition were observed under N-limited conditions, with several taxa strongly associated with individual genotypes. Notably, modern cultivars showed reduced SNF, which was also more prominent under low N availability, suggesting potential trade-offs associated with breeding for high-input systems. The line R99 exhibited a distinct microbial profile and reduced Rhizobium abundance, indicating a complex genotype–microbiome interaction. Conclusion These findings highlight the importance of both genotype and soil environment on bean performance and microbiome structure and underscore the need for breeding strategies aimed at improving N-use efficiency in bean production.

ABSTRACTHepatitis C virus (HCV) micro‐elimination faces challenges from fragmented care pathways, particularly in high‐prevalence regions with complex genotypes and socioeconomic barriers. This study evaluated a simplified ‘Test and Treat’ (TNT) strategy to enhance in‐hospital HCV micro‐elimination by reducing delays and improving linkage to care. Outcomes including HCV RNA testing rates, treatment uptake rates, time to treatment initiation and sustained virological response at 12 weeks (SVR12) of Pre‐TNT (Jan. 2022–Dec. 2022) and post‐TNT (Jan. 2023–Dec. 2024) were compared. Following TNT implementation, among 168,527 screened patients, the HCV RNA testing rate increased to 93.96% (2070/2203) from 68.17% under pre‐TNT, and the treatment rate among viremic patients rose to 81.98% (678/827) from 63.05%. The median time to treatment initiation was dramatically reduced from 12.5 to 3.8 days. SVR12 remained high, with a rate of 99.71%. Barriers among untreated patients were investigated via surveys and follow‐ups. Surveys of 500 HCV antibody positive patients revealed limited affordability (only 5% could bear costs > ¥8000) and low health literacy (only 39% knew about prevention and treatment). Among 149 untreated viremic patients, financial constraints and the perception that treatment was unnecessary while asymptomatic were key refusal reasons. The in‐hospital streamlined TNT strategy significantly improved HCV RNA testing linkage and treatment uptake, markedly reduced time to treatment initiation and achieved near‐universal cure, surpassing WHO treatment targets. Its effectiveness supports broader adoption in high‐prevalence regions, though complementary interventions addressing affordability and health literacy are needed for further progress.

Rotavirus A (RVA) is a leading cause of severe diarrhoea in children, and interspecies transmission significantly drives the genomic diversity of human RVAs. Cats represent a key host species, requiring in-depth analysis regarding RVA transmission to humans. This review evaluated the literature on the complex genotype constellations of feline RVAs in relation to relevant canine and human RVAs to define the role of feline RVAs in the evolutionary history of human strains. The review traces the methodological shift from genogrouping by RNA-RNA hybridisation to the current genotype constellation system enabled by whole-genome sequencing. While early methods identified a shared genomic closeness between human AU-1 and feline FRV-1, whole-genome sequencing indicated that several human RVA strains, including AU-1, HCR3A, and Ro1845, likely resulted from direct transmission of feline/canine strains, due to shared genotype constellations and high sequence identity with animal strains like feline FRV-1, Cat97 and canine CU-1. Evidence of reassortment-such as the emergence of G1P[9] and G9P[9] strains after the feline-derived G3P[9] crossed into the human population-suggests these feline-like strains have successfully overcome the host-species barrier and are capable of onward human-to-human transmission, not just dead-end spillover events. However, definitive confirmation of sustained transmission or contemporary spillover requires stringent phylogenetic criteria: multiple human strains with >99% identical sequences in a monophyletic lineage for sustained transmission, or an identical human-feline pair across all genome segments for contemporary spillover. Confirming the status of the AU-1-like constellation as a third, low-frequency human RVA type requires future studies applying these strict criteria.

The use of marker-associated selection methods in sheep allows to increase meat productivity indices in a short period of time. This requires genotyping for polymorphisms in various genes associated with growth and development of muscle tissue. Whole-genome association searches in sheep have identified a number of new candidate genes, one of which is FRY, which encodes a microtubule-associated protein. The study of the FRY gene structure based on the results of full genomic sequencing in Manych Merino sheep revealed more than 4800 polymorphisms of different types, most of which are represented by single nucleotide substitutions and are included in international databases. A significant association was found between complex genotype by polymorphisms of the FRY gene and most of the estimated lifetime parameters of meat productivity, such as live weight and body measurements. Analysis of the distribution of polymorphisms between the groups of studied animals allowed us to identify 21 single nucleotide substitutions, genotypes for which significantly differed in animals with high and low meat productivity. Most of these substitutions (19 SNPs) were located in introns of the gene, two polymorphisms were detected in exons. Animals with higher scores had homozygous genotypes for the common allele of the identified substitutions. Low performing individuals carried heterozygous and mutant homozygous genotypes. The identified single nucleotide polymorphisms can be used as molecular genetic markers in genotyping to predict meat productivity and in breeding work with merino sheep breeds.

Congenital fibrosis of the extraocular muscles type 3 (CFEOM3) is a congenital cranial dysinnervation disorder marked by variable ophthalmoplegia and ptosis with considerable phenotypic heterogeneity. We report a large multigenerational Iranian family with autosomal dominant CFEOM3. Affected individuals underwent comprehensive ophthalmologic evaluation. Whole-exome sequencing in the proband, followed by Sanger sequencing in ten affected and four unaffected relatives, identified a heterozygous missense variant, c.784C>T (p.Arg262Cys), in exon 4 of TUBB3 (16q24.3), which co-segregated with the disease phenotype. Cranial magnetic resonance imaging (MRI) in two affected individuals revealed asymmetric basal ganglia morphology, predominantly affecting the caudate nuclei and putamen. At the level of the anterior commissure, the bilateral CFEOM3 patient lacked a visible commissure, whereas the unilateral patient exhibited a thin but identifiable structure. Midline sagittal imaging demonstrated corpus callosum dysgenesis in both individuals, with slightly greater involvement of the corpus callosum body in the unilateral case, though this difference was not radiologically significant. Despite differences in ocular phenotype, overall cerebral involvement was largely comparable. These findings confirm the pathogenic role of the TUBB3 p.Arg262Cys variant in CFEOM3A and extend the spectrum of ophthalmologic and neuroimaging abnormalities within an extended family. The results highlight the complex genotype–phenotype relationships in TUBB3-related disease and underscore the importance of integrated clinical and molecular evaluation for precise diagnosis.

Abstract Olfactory cues play a vital role in mammalian social communication, conveying fitness-relevant information such as genetic quality and relatedness. Kin recognition through scent can help avoid inbreeding and guide nepotistic behaviors, enhancing fitness. In banded mongooses, synchronized breeding disrupts familiarity-based kin recognition, potentially increasing reliance on phenotype matching, where individuals compare genetically determined odors to assess similarity. We tested whether banded mongooses use odors to assess genetic diversity and relatedness based on (1) major histocompatibility complex (MHC) genotypes and (2) neutral microsatellite loci. Results showed individuals responded differently to odors from unfamiliar conspecifics based on MHC diversity and relatedness. Specifically, less MHC-diverse and less related individuals attracted more interest, suggesting odor cues are used to evaluate intruder or competitor threat levels. Neutral genetic diversity did not affect odor responses and was not correlated with MHC diversity, indicating responses to MHC diversity are independent of overall genetic diversity. No effect of MHC similarity was observed, possibly due to sample size limitations. Our findings suggest MHC diversity may signal genetic quality, while other genomic regions might contribute to assessing relatedness. These results provide a foundation for further research into the role of MHC and other genes in social communication in species where phenotype matching offers adaptive benefits.

In modern dairy farming, the study of genetic factors affecting the productive longevity and milk productivity of cattle is relevant. The leptin gene, involved in the regulation of energy metabolism, is a promising marker for selection. However, the influence of its polymorphism complex genotypes (A80V, R25C, Y7F) on the productivity and longevity of animals has not been sufficiently studied, which determines the importance of this research. The aim of the study was to investigate the influence of the leptin gene complex genotypes at sites A80V, R25C, Y7F on the milk productivity indicators and the duration of economic use of Kholmogory cattle. The study was conducted on 207 Kholmogory breed cows, divided into groups with different complex genotypes. For statistical analysis, the number of animals in the compared groups was equalized: 13 heads per group for the study of lifetime milk productivity and 19 heads per group for the assessment of the duration of use. Genotyping was performed by PCR-RFLP, and statistical processing was carried out using non-parametric methods (Mann - Whitney U test). Lifetime daily milk yield, milk fat and protein content, age at culling, and lifetime milking days (LMD) were analyzed. It was revealed that the AVRCYY genotype is associated with the maximum daily milk yield (22.04 kg) and the highest number of LMD (2032 days), indicating its positive influence on productive longevity. The lowest indicators were noted for the AVCCYY genotype (194 LMD). Significant differences in milk fat content were found between groups AACCYY, AARCYY, AARRYY, and AVCCYY. The AACCYY genotype showed the highest protein content (3.23%), but the lowest milk yield. Differences in the structure of culling reasons were also identified: gynecological diseases prevailed in animals with the AVCCYY genotype combination, while limb diseases prevailed in animals with the AVRCYY complex genotype. The results of the study demonstrate the significance of a comprehensive analysis of leptin gene genotypes for dairy cattle selection. The AVRCYY genotype can be recommended as a marker for increased productive longevity.

Thalassemia is a genetic blood disorder caused by disrupted hemoglobin synthesis, posing significant public health challenges. This study aims to expand the identification of novel thalassemia variants in a large cohort from pre-marriage screenings in Ganzhou, Southern Jiangxi, China. Data from 229 246 individuals screened through Next-Generation Sequencing (NGS) from 2019 to 2022 led to the identification of 180 participants with novel variants, marking the first large-scale documentation of such variations in the population. Among them, 51.1% were male with a mean age of 27 years, and the frequency of novel thalassemia variants was 0.079%. We uncovered 180 novel variants, including 68 α-thalassemia variants across 33 types (0.0297% frequency) and 112 β-thalassemia variants belonging to 40 unique types (0.0489% frequency). The most common α-thalassemia genotype was HBA1:c.95 + 9C > T at 17.65%, while HBB:c.-180G > C was most prevalent among β-thalassemia variants at 23.21%. Ten novel α-thalassemia variants were linked to mild α-thalassemia, and clinical phenotypes were documented for 21 complex genotypes. This study catalogues 73 novel variants and highlights the genetic diversity of thalassemia, informing future preventive strategies.

The TNFα content in the blood serum of 109 patients with uterine fibroids was studied. Cytokine concentrations ranged from 4.65 to 25.88 pg/ml regardless of the clinical parameters of the disease, but were associated with complex genotypes of different structural and functional organization (TNFA, IL1B, IL4, IL6, IL8, IL10, IL17A, VEGFA, MMP2, MMP3, MMP9). The interaction of multiple genes that affect the level of serum TNFα production has been revealed. In particular, on the one hand, the complex genotype TNF-308GG/VEGF-2578CA is positively associated with high levels of TNFα (OR = 10.00, pcor = 0.0274), and on the other hand, the combined genotype of 4 polymorphisms TNF-308GG/TNF-238GG/VEGF-2578AA/MMP2-1306CC is closely associated with its low level (OR = 25.00, pcor = 0.0469). The obtained results allow better understand the mechanisms of the manifestation of the genetic predisposition to uterine fibroids associated with the presence in the genome of highly specific gene compositions that underlie tumorogenesis in this disease.

Background: Congenital heart disease (CHD) is the most common birth defect globally, yet its genetic underpinnings remain incompletely understood. Since the introduction of CRISPR/Cas9, gene editing has emerged as a transformative tool for modeling and potentially treating CHD. However, no consolidated review exists mapping the scope of CRISPR/Cas9-based applications in this domain. Research Question: What genes, models, and delivery strategies have been used in CRISPR/Cas9-based CHD research over the past 15 years, and what are the major outcomes and translational gaps? Methods: We conducted a scoping review following PRISMA-ScR guidelines. PubMed, Web of Science, and Embase were searched for studies published between 2010–2025 that utilized CRISPR/Cas9 in CHD-related gene editing. Inclusion criteria encompassed human-induced pluripotent stem cell (hiPSC) models and animal systems (e.g., mice, zebrafish) focused on either disease modeling or therapeutic correction of known CHD-associated genes. Results: A total of 87 studies met inclusion criteria. In human hiPSC models, CRISPR was primarily used to introduce or correct mutations in key CHD genes ( NKX2-5, GATA4, TBX5, MYH6, NOTCH1 ), enabling mechanistic insights and phenotypic rescue in cardiomyocytes. In animal models, CRISPR/Cas9 created disease-relevant knockouts or knock-ins across species such as mice, zebrafish, and medaka. Notably, therapeutic editing was successfully demonstrated in neonatal mice using AAV9-mediated somatic CRISPR to correct PRKAG2 and DMD mutations. However, few studies addressed polygenic inheritance, in utero delivery, or long-term safety. Tables 1 and 2 summarize the genes, models, editing purposes, delivery methods, and outcomes. A conceptual figure maps the landscape of CRISPR applications in CHD. Conclusion: CRISPR/Cas9 has revolutionized CHD research, enabling precise modeling and first steps toward somatic correction in preclinical systems. Nonetheless, significant translational barriers remain, including delivery challenges, modeling of complex genotypes, and ethical concerns with prenatal editing. Future studies integrating base editing, 3D cardiac organoids, and multiplex gene targeting may overcome current limitations. This scoping review identifies critical gaps and serves as a roadmap for accelerating genome-editing-based CHD therapeutics.

Comparative studies of the origin of the pool red Gorbatov breed (n = 129) with world breeds of red root cattle were conducted. With the similarity coefficient K = 2, animals of the desired breed differed to the greatest extent from the red Belarusian cattle, Holstein black and redmotley color, red Danish (including the gene pool group), but were more similar in genomic components to the red steppe and Suksun breeds. With K = 4, the greatest homogeneity of the red Gorbatov cattle groups was observed, and with K = 6–10, strong fragmentation in the form of complex genotypes with other compared breeds was noted. It was found that the highest frequency of haplotype clusters was localized on chromosome 6 of cattle for 6 compared red root breeds (37196103–37698422 bp, detectable region), as well as on chromosome 7 of cattle for 6 compared breeds (530447:1915174 bp, detectable region). Analysis of genome regions by QTL showed that the ROH/Fst, hapflk/Fst and hapflk/ROH genes identified by different methods were associated with the fatty acid composition of milk (including conjugated FA), body weight and size of animals, average daily weight gain and feed intake, eye muscle area, milk fat and protein yield, fertility indicators (calving difficulty). A more detailed examination of the LD values by breed and chromosomes at distances of 0–30 kb, 30–70 kb, 70–100 kb and 100–200 kb at r2 > 0.30 revealed pairs of SNPs in fractional terms, most often found on the chromosomes of cattle BTA6, BTA9, BTA14.

Traditional selection in cattle heavily relies on linear mixed models (BLUP), which are effective but limited in modeling non-linear genetic interactions (epistasis). Machine learning (ML) algorithms offer an alternative capable of detecting complex dependencies in genetic data. The aim of this work was to test the Support Vector Regression (SVR) methodology for predicting milk productivity and to develop a "reverse engineering" approach to identify optimal allelic combinations based on a limited and heterogeneous set of genetic markers. The study was conducted on a sample of 81 Ukrainian Red-and-White dairy cows. Genotypes for 3 QTLs (PRL, LEP, TNF-α) were used, which were transformed into 12 binary features (One-Hot encoding). Milk yield (305 days) and fat content (kg) were used as target variables for building the SVR model. The target variable (milk yield) was standardized using StandardScaler. The model was trained using 5-fold cross-validation with hyperparameter tuning (GridSearchCV), comparing both non-shuffled and shuffled data splits. A synthetic "solution space" (54 combinations) was generated to identify "ideal" genotypes, which was then analyzed by the trained SVR model. Three-way ANOVA did not reveal a statistically significant (p < 0.05) effect of the main factors (PRL, LEP, TNF-α) or their interactions on milk yield, although PRL showed a borderline trend (p=0.055). SVR models trained on non-shuffled data failed, yielding negative R² values (down to -0.066), indicating overfitting. However, the model using all 3 markers (12 features) combined with 5-fold cross-validation with shuffling (shuffle=True) achieved the best, albeit practically negligible, positive result (R² = 0.0064) using a non-linear ’rbf’ kernel, with an estimated RMSE of ~790 kg. The "reverse engineering" approach identified hypothetical complex genotypes (Top 3: CC-CC-AD, CT-CC-AD, CC-CC-AB) with a predicted yield (up to 5173 kg) significantly higher than the herd average (4838 kg). The study confirmed the methodological suitability of SVR for analyzing heterogeneous genetic data and "reverse engineering" selection goals, even on a critically small sample (n=81). The low R² values highlight that the primary limitation is the small sample size relative to the number of features, which prevents the model from capturing reliable predictive signals. This approach serves as a powerful analytical complement to traditional BLUP methods, providing a framework for identifying desirable "genetic formulas" for targeted selection once larger datasets become available. Keywords: machine learning (ML), support vector regression (SVR), prediction, genetic markers, dairy cattle productivity.

Short tandem repeats (STRs) are a rich source of genetic variation, but are difficult to genotype. While specialized repeat variant callers exist, they typically assume a euploid human genome. This means recent findings regarding phenotypic effects of STR variants in human health and disease cannot be readily extended to polyploid organisms or cancer, which is characterised by copy number alterations (CNAs). Here we present ConSTRain, a novel STR variant caller that explicitly accounts for the copy number of loci in its genotyping approach. We benchmark ConSTRain using a euploid human 100X whole genome sequencing sample where it calls STR allele lengths for over 1.7 × 106 loci in under 20 minutes with an accuracy of 98.28%. Subsequently, we show that ConSTRain resolves complex STR genotypes in an artificial trisomy 21 sample and a polyploid Dwarf Cavendish banana harbouring a large duplication. Finally, we analyse a microsatellite instable colorectal cancer tumoroid, where ConSTRain tackles CNAs and whole-genome duplications. ConSTRain is the first STR variant caller that allows for the investigation of repeats affected by CNAs, aneuploidies, and polyploid genomes. This unlocks the investigation of STRs across a wide range of contexts and organisms where they previously could not be easily studied.

ABSTRACTThe growing interest in high‐biomass sorghum (Sorghum bicolor L. Moench), hereafter referred to as sorghum, as a bioenergy feedstock in the United States requires an understanding of geographical adaptation to identify the most suitable hybrids for the Midwest. In this study, 13 sorghum hybrids (H1–H13) were evaluated for biomass yield potential in central and southern IL over two growing seasons (2022 and 2023). In addition to biomass yield, the effects of nitrogen (N) fertilization on yield, nutrient removal (N, P, and K), and feedstock composition (cellulose, hemicellulose, lignin, and soluble fractions) were determined to identify the best‐performing sorghum hybrid across environmental gradients. The experimental design was a split‐plot arrangement within a randomized complete block design with four replications at each of two locations: N rates (0 and 112 kg‐N ha−1) as a whole plot factor and 13 sorghum hybrids as a subplot factor. As a result, complex genotypes (13 hybrids) by environment (2 sites and 2 years) and management (2 N rates) interactions were observed in biomass yield. The best hybrids at both sites were H1 (ATx2932/F10702_PSL) and H13 (TX08001), which were very photoperiod sensitive (PS). These hybrids produced superior biomass yield, and they also exhibited less nutrient removal and high energy‐rich feedstock compositions (cellulose, hemicellulose, and lignin). Biomass yield potential was associated with morphological and phenological traits according to environmental conditions. Low‐yielding hybrids were short‐stature (H5 and H6) with pollinators (F10801_PSL‐3dw and F10805_PSL‐3dw) that are recessive at the Dw3 locus. Moderate PS hybrids (H7, H8, H11, and H12) that produced grain panicles at harvest showed high biomass yield plasticity and excessive nutrient removal as they accumulated high K concentrations in biomass tissues and high N and P in grain panicles.

Factor XI (FXI) deficiency, or hemophilia C, is a rare bleeding disorder resulting from reduced levels or dysfunctional FXI protein due to mutations in the F11 gene. This study investigated the correlation between FXI activity levels, F11 genotype, and bleeding phenotypes. Clinical and genetic characteristics of 93 individuals from southern Italy diagnosed with congenital FXI deficiency, including 39 index cases and their relatives, were evaluated. FXI:C plasma levels were measured. Sanger sequencing of F11 was performed, and the pathogenicity of variants identified was assessed using in silico tools. FXI activity levels ranged widely (1–69%), with most cases being heterozygous and showing moderate deficiency. Only 12 individuals had severe FXI deficiency, typically associated with homozygosity or compound heterozygosity. Bleeding symptoms varied from mild to severe and occurred in 31% of subjects, though only a minority of those with severe deficiency experienced spontaneous or surgery-related bleeding. Sanger sequencing revealed 24 distinct F11 gene variants, predominantly missense mutations, with three novel variants (p.Val89*, p.Leu306Pro, and p.Trp515Gly). Common mutations included p.Glu135* and p.Glu315Lys. Variants were distributed across the gene, with no domain-specific clustering. No clear genotype–phenotype correlation was observed. FXI levels alone did not reliably predict bleeding risk, highlighting the influence of additional factors such as age, gender, and clinical history. This study reinforces the allelic and clinical heterogeneity of FXI deficiency and the limited utility of FXI:C levels alone for predicting bleeding severity. Further research is needed to clarify the complex genotype–phenotype relationships in FXI deficiency.

This study investigates the complex genotype × treatment × environment (G×T×E) interactions driving soybean seed biochemical trait expression under salicylic acid (SA) application and water stress conditions. Using a comprehensive dataset of 55,450 observations across 13 agronomic and biochemical traits, six soybean genotypes were subjected to factorial combinations of SA (250 mg and 400 mg) and water stress (5%, 70%, and ambient field capacity). Trait responses were quantified via machine learning sensitivity analysis, three-way ANOVA, and structural equation modeling (SEM). Results reveal that genotype exerted the dominant influence across traits, followed by water stress and SA, with several traits chlorophyll concentrations, sugars, and protein contents exhibiting strong three-way interaction effects. Notably, genotypes G3 and G5 showed superior biochemical plasticity and yield stability, while G6 prioritized stress resilience at the expense of productivity. Moderate drought induced beneficial hormetic shifts in biochemical traits, and SA treatments enhanced pigment and protein expression in a genotype-dependent manner. Findings provide mechanistic insight and a scalable framework for genotype-tailored agronomy and biochemical trait optimization in soybeans.

Application of Third-Generation Sequencing Technology in RHD Genotyping of a Chinese Pedigree with Weak D Phenotype

Objective. To reveal the influence of complex genotypes of beta-casein and kappa-casein genes on milk productivity indices of Kholmogorsk cows. Methods. DNA extraction was carried out using the reagent kit “MagnoPrime VET”. Allele-specific PCR (AS-PCR) was used to determine allele polymorphism of CSN2 gene. Determination of DNA restriction fragments by visualizing the results by horizontal electrophoresis with 3% agarose gel. Restriction fragment length polymorphism (PCR-PDRF) was used to determine the A and B alleles of the CSN3 gene. Results. In the course of molecular genetic analysis of Kholmogor breed animals, polymorphism of genetic variants of beta-casein (CSN2) and kappa-casein (CSN3) proteins was detected, and the frequency of occurrence of different complex genotypes was studied. The most common complex genotype was found to be A1A2/AA, occurring in 41.15% of the animals, representing 158 individuals. The least common genotype combinations were A1A1/BB and A1A2/BB with a total number of 8 animals (less than 2.5%). No individuals with A2A2/BB genotypes were found. Animals with a combination of A2A2/AA genotypes had the best milk yield, fat mass fraction, protein mass fraction, milk fat quantity and milk protein quantity among heifer cows. The lowest values for mass fraction of protein, milk fat and milk protein had animals with A1A1/AB genotype combination. Among all the studied herd, cows with complex genotype A2A2/AA had the best result in many indicators of milk productivity. Whereas the lowest signs of milk productivity were shown by animals with a combination of A1A1/ BB genotypes. Scientific novelty consisted in the study of the relationship between the complex genotypes of betacasein, kappa-casein genes and their influence on milk productivity of Kholmogorsk cows. At the moment, there are very few scientific works devoted to the study of complex genotypes of these genes, and there are no studies conducted on the Kholmogorsk breed of cattle.

Cas12a mice enable the rapid generation of highly complex tumour genotypes.

Many biological experiments involve studying the differences caused by genetic modifications, including genotypes composed of modifications at more than 1 locus. However, as the genotypes increase in number and complexity, it becomes a major challenge to independently generate and track the necessary number of biological replicate samples. A major development in genetic studies of large numbers of genotypes has been the use of barcode tracking. Inspired by such high-throughput studies, we developed a barcode-based method to track large numbers of independent replicates of a small number of combinatorial genotypes in a pooled format, enabling robust detection of subtle phenotypic differences. To construct a plasmid library of combinatorial genotypes, we utilized a nested serial cloning process to combine gene variants of interest that have associated DNA barcodes. The final plasmids each contain variants of multiple genes of interest, and a combined barcode that specifies the genotype of all the genes while also encoding a random sequence for tracking individual replicates. Sequencing of the pool of barcodes by next-generation sequencing allows the whole population to be studied in a single flask, enabling a high degree of replication even for complex genotypes. Using this approach, we tested the functionality of combinations of yeast, human, and null orthologs of the nucleotide excision repair factor I (NEF-1) complex and found that yeast cells expressing all 3 yeast NEF-1 subunits had superior growth in DNA-damaging conditions. We also assessed the sensitivity of our method by simulating downsampling of barcodes across different degrees of phenotypic differentiation. Our results demonstrate the utility of NICR (nested identification combined with replication) barcodes for high-throughput combinatorial genetic screens and provide a scalable framework for exploring complex genotype-phenotype relationships.