Accelerated discovery and miniaturization of novel single-stranded cytidine deaminases.

Cytidine base editors (CBEs) hold significant potential in genetic disease treatment and in breeding superior traits into animals. However, their large protein sizes limit their delivery by adeno-associated virus (AAV), given its packing capacity of <4.7 kb. To overcome this, we employed a web-based fast generic discovery (WFG) strategy, identifying several small ssDNA deaminases (Sdds) and constructing multiple Sdd-CBE 1.0 versions. SflSdd-CBE 1.0 demonstrated high C-to-T editing efficiency, comparable to AncBE4max, while SviSdd-CBE 1.0 exhibited moderate C-to-T editing efficiency with a narrow editing window (C3 to C5). Utilizing AlphaFold2, we devised a one-step miniaturization strategy, reducing the size of Sdds while preserving their efficiency. Notably, we administered AAV8 expressing PCSK9 targeted sgRNA and SflSdd-CBEs (nSaCas9) 2.0 into mice, leading to gene-editing events (with editing efficiency up to 15%) and reduced serum cholesterol levels, underscoring the potential of Sdds in gene therapy. These findings offer new single-stranded editing tools for the treatment of rare genetic diseases.

Whole genome sequencing identified genomic diversity and candidated genes associated with economic traits in Northeasern Merino in China.

Introduction: Northeast Merino (NMS) is a breed developed in Northeast China during the 1960s for wool and meat production. It exhibits excellent traits such as high wool yield, superior meat quality, rapid growth rate, robust disease resistance, and adaptability to cold climates. However, no studies have used whole-genome sequencing data to investigate the superior traits of NMS. Methods: In this study, we investigated the population structure, genetic diversity, and selection signals of NMS using whole-genome sequencing data from 20 individuals. Two methods (integrated haplotype score and composite likelihood ratio) were used for selection signal analysis, and the Fixation Index was used to explore the selection signals of NMS and the other two breeds, Mongolian sheep and South African meat Merino. Results: The results showed that NMS had low inbreeding levels, high genomic diversity, and a pedigree of both Merino breeds and Chinese local breeds. A total length of 14.09 Mb genomic region containing 287 genes was detected using the two methods. Further exploration of the functions of these genes revealed that they are mainly concentrated in wool production performance (IRF2BP2, MAP3K7, and WNT3), meat production performance (NDUFA9, SETBP1, ZBTB38, and FTO), cold resistance (DNAJC13, LPGAT1, and PRDM16), and immune response (PRDM2, GALNT8, and HCAR2). The selection signals of NMS and the other two breeds annotated 87 and 23 genes, respectively. These genes were also mainly focused on wool and meat production performance. Conclusion: These results provide a basis for further breeding improvement, comprehensive use of this breed, and a reference for research on other breeds.

Identification of genomic diversity and selection signatures in Luxi cattle using whole-genome sequencing data.

OBJECTIVE: The objective of this study was to investigate the genetic diversity, population structure and whole-genome selection signatures of Luxi cattle to reveal its genomic characteristics in terms of meat and carcass traits, skeletal muscle development, body size, and other traits. METHODS: To further analyze the genomic characteristics of Luxi cattle, this study sequenced the whole-genome of 16 individuals from the core conservation farm in Shandong region, and collected 174 published genomes of cattle for conjoint analysis. Furthermore, three different statistics (pi, Fst, and XP-EHH) were used to detect potential positive selection signatures related to selection in Luxi cattle. Moreover, gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were performed to reveal the potential biological function of candidate genes harbored in selected regions. RESULTS: The results showed that Luxi cattle had high genomic diversity and low inbreeding levels. Using three complementary methods (pi, Fst, and XP-EHH) to detect the signatures of selection in the Luxi cattle genome, there were 2,941, 2,221 and 1,304 potentially selected genes identified, respectively. Furthermore, there were 45 genes annotated in common overlapping genomic regions covered 0.723 Mb, including PLAG1 zinc finger (PLAG1), dedicator of cytokinesis 3 (DOCK3), ephrin A2 (EFNA2), DAZ associated protein 1 (DAZAP1), Ral GTPase activating protein catalytic subunit alpha 1 (RALGAPA1), mediator complex subunit 13 (MED13), and decaprenyl diphosphate synthase subunit 2 (PDSS2), most of which were enriched in pathways related to muscle growth and differentiation and immunity. CONCLUSION: In this study, we provided a series of genes associated with important economic traits were found in positive selection regions, and a scientific basis for the scientific conservation and genetic improvement of Luxi cattle.

Detection of genomic variations and selection signatures in Wagyu using whole-genome sequencing data.

Wagyu is recognized for producing marbled beef with high nutritional value and flavor. Reportedly, Wagyu has been widely used to improve the meat quality of local breeds around the world. However, studies on the genetic mechanism of meat quality in Wagyu at the whole-genome level are rarely reported. Here, whole-genome sequencing data of 11 Wagyu and 115 other individuals were used to explore the genomic variations and genes under selection pressure in Wagyu. A total of 31 349 non-synonymous variants and 53 102 synonymous variants were identified in Wagyu. The population structure analysis showed that Wagyu had the closest genetic relationship with Mishima-Ushi cattle and was apparently separated from other cattle breeds. Then, composite likelihood ratio (CLR), integrated haplotype score, fixation index and cross-population composite likelihood ratio (XP-CLR) tests were performed to identify the candidate genes under positive selection in Wagyu. In total, 770 regions containing 312 genes were identified by at least three methods. Among them, 97 regions containing 27 genes were detected by all four methods. We specifically illustrate a list of interesting genes, including LRP2BP, GAA, CACNG6, CXADR, GPCPD1, KLF2, KLF13, SOX5, MYBPC1, SLC25A10, ATP8A1 and MYH15, which are associated with lipid metabolism, fat deposition, muscle development, bone development, feed intake and growth traits in Wagyu. This is the first study to explore the genomic variations and selection signatures of Wagyu at the whole-genome level. These results will provide significant help to beef cattle improvement and breeding.

Assessing Genomic Diversity and Signatures of Selection in Chinese Red Steppe Cattle Using High-Density SNP Array.

Chinese Red Steppe Cattle (CRS), a composite cattle breed, is well known for its milk production, high slaughter rate, carcass traits, and meat quality. Nowadays, it is widely bred in Jilin and Hebei Province and the Inner Mongolia Autonomous region. However, the population structure and the genetic basis of prominent characteristics of CRS are still unknown. In this study, we systematically describe their population structure, genetic diversity, and selection signature based on genotyping data from 61 CRS individuals with GGP Bovine 100 K chip. The results showed that CRS cattle had low inbreeding levels and had formed a unique genetic structure feature. Using two complementary methods (including comprehensive haplotype score and complex likelihood ratio), we identified 1291 and 1285 potentially selected genes, respectively. There were 141 genes annotated in common 106 overlapping genomic regions covered 5.62 Mb, including PLAG1, PRKG2, DGAT1, PARP10, TONSL, ADCK5, and BMP3, most of which were enriched in pathways related to muscle growth and differentiation, milk production, and lipid metabolism. This study will contribute to understanding the genetic mechanism behind artificial selection and give an extensive reference for subsequent breeding.

Identification of Potential Early Diagnostic Biomarkers of Sepsis.

OBJECTIVE: The goal of this article was to identify potential biomarkers for early diagnosis of sepsis in order to improve their survival. METHODS: We analyzed differential gene expression between adult sepsis patients and controls in the GSE54514 dataset. Coexpression analysis was used to cluster coexpression modules, and enrichment analysis was performed on module genes. We also analyzed differential gene expression between neonatal sepsis patients and controls in the GSE25504 dataset, and we identified the subset of differentially expressed genes (DEGs) common to neonates and adults. All samples in the GSE54514 dataset were randomly divided into training and validation sets, and diagnostic signatures were constructed using least absolute shrink and selection operator (LASSO) regression. The key gene signature was screened for diagnostic value based on area under the receiver operating characteristic curve (AUC). STEM software identified dysregulated genes associated with sepsis-associated mortality. The ssGSEA method was used to quantify differences in immune cell infiltration between sepsis and control samples. RESULTS: A total of 6316 DEGs in GSE54514 were obtained spanning 10 modules. Module genes were mainly enriched in immune and metabolic responses. Screening 51 genes from among common genes based on AUC > 0.7 led to a LASSO model for the training set. We obtained a 25-gene signature, which we validated in the validation set and in the GSE25504 dataset. Among the signature genes, SLC2A6, C1ORF55, DUSP5 and RHOB were recognized as key genes (AUC > 0.75) in both the GSE54514 and GSE25504 datasets. SLC2A6 was identified by STEM as associated with sepsis-associated mortality and showed the strongest positive correlation with infiltration levels of Th1 cells. CONCLUSION: In summary, our four key genes may have important implications for the early diagnosis of sepsis patients. In particular, SLC2A6 may be a critical biomarker for predicting survival in sepsis.