To extend storage/shelf life, pH-related candidate genes were mined to provide new opportunities for genetic improvement. We obtained candidate genes related to pH through a genome-wide association analysis to provide research directions for extending meat storage/shelf life.45min, pH24h, pH48h and pH72h) of the longissimus dorsi muscles in F2 individuals of 462 Texel sheep × Altay sheep were determined, genotyping was performed using Illumina Ovine SNP 600 K BeadChip and whole genome resequencing technology, a genome-wide association analysis (GWAS) was used to screen the candidate genes and molecular markers for pH values related to the quality traits of mutton, and the effects of population stratification were detected by Q–Q plots. The results showed that the pH population stratification analysis did not find significant systemic bias, and there was no obvious population stratification effect. The results of the association analysis showed that 28 SNPs significantly associated with pH reached the level of genomic significance. The candidate gene associated with pH45min was identified as the CCDC92 gene by gene annotation and a search of the literature. Candidate genes related to pH24h were KDM4C, TGFB2 and GOT2 genes. The candidate genes related to pH48h were MMP12 and MMP13 genes. The candidate genes related to pH72h were HILPDA and FAT1 genes. Further bioinformatics analyses showed 24 gene ontology terms and five signaling pathways that were significantly enriched (p ≤ 0.05). Many terms and pathways were related to cellular components, processes of protein modification, the activity of protein dimerization and hydrolase activity. These identified SNPs and genes could provide useful information about meat and the storage/shelf life of meat, thereby extending the storage/shelf life and quality of meat.pH was one of the important meat quality traits, which was an important factor affecting the storage/shelf life and quality of meat in meat production. In order to find a way to extend the storage/shelf life, the pH values (pH With the continuous improvement of people’s living standards, meat quality has attracted more and more attention from farmers and consumers. Farmers not only need to increase the yield of mutton, but also must constantly improve the quality of mutton. As one of the most important evaluation indexes of meat quality traits , pH is aSince the application of the 600 K SNP commercial chip and whole genome resequencing in sheep, researchers in China and abroad have conducted genome-wide association analyses on various traits of sheep, such as the characteristics of the meat , reproduTherefore, the objectives, in our study, are as follows: the pH values of the longissimus dorsi muscle at 45 min, 24 h, 48 h and 72 h after slaughter were measured. Next, the sheep 600 K chip technology and whole-genome resequencing technology were used to conduct a GWAS study in order to find the significant SNP sites that affected pH, and using the SNPs positions to identify candidate genes and pathways that may influence traits of pH. In addition, we will use the identified genes to conduct some bioinformatics analyses, such as gene ontology and the KEGG pathway for further analyses.1 individuals were produced using 3 pure-bred Texel sheep from New Zealand as the male parents and 220 Altay sheep as the female parents. Moreover, 4 F1 rams and 116 ewes were chosen to build the F1 population. From autumn 2014 to autumn 2019, 395 Crossbred F2 individuals and 67 backcrossed F2 individuals were produced by crossing (F1 rams × F1 ewes) and backcrossing (F1 raws × Altay ewes), using the simultaneous estrus and artificial insemination techniques with four F1 rams as the sires. After excluding individuals with incomplete information and abnormal development, 462 meat quality traits were scored and determined. SNP microarray genotyping was performed for 246 individuals, and whole-genome resequencing was performed for 216 individuals. Among them, 462 individuals of the F2 cross were developed as an F2 resource population managed by professional breeders. The conditions, forage materials and feeding methods used in each enclosure were the same for all six years. Samples from slaughtered animals were taken at the same time each year.The experimental animals were procured from the Sheep Breeding Experimental base of the Xinjiang Academy of Animal Science . In 2012, FAll the experimental sheep were fed up to 8 months of age, and the live weight was measured before slaughter at the modern slaughterhouse of Hualing in Urumqi. Simultaneously, we sent the mutton to the dissection workshop for dissection of the carcass. Later, samples from the 12th to 13th ribs ofthe longissimus dorsi muscle on the left side of the carcass were collected to assess the traits of muscle pH. 2 individuals were collected. The pH was measured 45 min, 24 h, 48 h and 72 h after slaughter, and the samples were stored in a refrigerator at 4 °C between measurements. The pH was measured with a portable handheld pH meter purchased from TESTO, Germany. Each sample was measured 3 times, and the average was used as the final result [45min, pH24h, pH48h and pH72h. SPSS19.0 was used for the statistical analyses of the phenotypic data, and the correlation coefficients between the phenotypes were calculated.Longissimus dorsi muscles from the 12th to 13th ribs of the carcass of Texel sheep × Altay sheep Fl result . In tota2 population of the Texel sheep × Altay sheep had ear tags applied within 24 h after birth. At the age of 2 months, tattoos were applied to the other ear with tattooing forceps, and the ear tags and tattoos were recorded. Individuals of the F2 individuals were sent to Beijing Compson Biotechnology Co., Ltd. , the DNA of 246 individuals was detected by Illumina Ovine SNP 600 K BeadChip and the DNA of 216 individuals was detected by whole genome resequencing (different sampling time was the main factor that caused different detection methods). Afterwards, the combination of chip data and resequencing data and the missing parts were filled with the genotype using beagle software. A total of 980,383 SNPs were obtained from 461 individuals. Subsequently, Plink1.9 [Meanwhile, ear tissue specimens were collected and placed in 2 mL preservation tubes (containing 75% ethanol), and then stored at −20 °C for future use. The genomic DNA of the ear tissue was extracted, and the concentration and purity of the samples were determined by a Nanodrop 2000 spectrophotometer. The qualified DNA samples were evenly diluted to 50 ng/μL. The DNA from the ear tissue of 462 qualified Texel sheep × Altay sheep FW is the vector matrix of the fixed effect, α is the vector of the fixed effects, ig was the vector of the genetic effects, ig = iu is the additive effect of the ith SNPs and zij is the correlation coefficient of the allele frequency. The estimation of PVE was equivalent to calculating the heritability of SNPs, namely GCTA v1.93.2 software  was usedIn order to detect the population structure of the population samples, a principal component analysis was performed on the genotype data from 461 individuals. The GCTA v1.93.2 software ,19 was uGEMMA software was used for the GWAS analysis ,21. A miThe analytical model was:In the GWAS analysis, the effects of the population stratification effect can lead to false positive results . It is nThe sheep reference genome Ovis_aries_v3.1 was used to physically annotate the significant SNPs found in the GWAS and to identify candidate genes. The SNP databases of the UCSC and NCBI websites were used to determine the chromosomes and physical locations of the significantly-related SNP loci, and the ANNOVAR software ,25,26 waThe standard databases were used for the Gene Ontology (GO) terms  and Kyot45min, pH24h, pH48h and pH72h) of the longissimus dorsi muscle samples of 462 F2 individuals collected from the experimental base from 2014 to 2019 were determined. The descriptive statistics included the mean, maximum, minimum and coefficient of variation. The phenotypic measurements of these traits were shown in 45min was 5.98, that of pH24h was 5.66, that of pH48h was 5.63 and that of pH72h was 5.47. Between 45 min and 72 h after slaughter, the pH value of the samples showed a decreasing trend at 4 °C; the pH decreasing trend was the same as that reported in the literature [The pH values . There was a significant positive correlation between pH48h and pH72h .As can be seen from After controlling the quality with Plink software, according to quality control standards, 461 individuals and 613,178 SNP loci were retained for the subsequent GWAS association analysis. See the 45min was 0.3259. The phenotypic contribution rate of ten significant SNP sites for pH24h was 0.2754. The phenotypic contribution rate of six significant SNP sites for pH48h was 0.4452. The phenotypic contribution rate of seven significant SNP loci for pH72h was 0.6129, and the phenotypic contribution rate of the significant loci in pH72h was the highest among the four traits.The PVE analyses of 28 sites significantly correlated with pH selected by GWAS were performed, and the results were shown in 2 population after quality control, and a cluster analysis was conducted using the first three principal components . Each point in the PCA map represents a sample, and the aggregation of the grouped samples indicated that the differences among these samples were small, while a greater distance between groups indicated that the differences among these samples were large. Based on the genomic data, PCA was performed on 613,178 SNP loci from all samples of the FThe results of detecting the effects of population stratification effect detection are shown in p < 8.15 × 10−8), a secondary GWAS signal was identified (p < 1 × 10−5) [p) >5. The GWAS results for pH are listed in p-values of the association. The QQMan software package of R was used to draw the Manhattan plots and visualize the results of the association analysis of pH in each time period [In the GWAS of pH, although no signal exceeded the Bonferroni significance threshold of GWAS ( × 10−5) . Thus, te period .45min were located on chromosomes 1, 13, 17, 18 and 25; 10 SNPs significantly associated with pH24h were located on chromosomes 2, 3, 8, 12 and 14; six SNPs significantly associated with pH48h were located on chromosomes 3, 15, 20 and 23; and seven SNPs significantly associated with pH72h were located on chromosomes 3, 4, 6, 16 and 26, respectively.In total, 28 SNPs significantly correlated with pH were detected by the genome-wide association analysis. Among these, five SNPs significantly correlated with pHUsing the UCSC Genome browser and NCBI database through the Asian server for the sheep reference genome Ovis_aries_v3.1, 36 genes were obtained within the region of 2 Mb up/downstream of the significant SNPs for pH traits.45min. There were 301 GO entries and 65 KEGG pathways for pH24h, among which 19 GO entries and 1 KEGG pathway were enriched significantly (p < 0.05). There were 244 GO terms and 17 KEGG pathways found for pH48h, among which 5 GO terms and 3 KEGG pathways were significantly enriched (p < 0.05). The results for pH72h included 287 GO terms and 27 KEGG pathways, in which 1 KEGG pathway was significantly enriched (p < 0.05).Through the GO and KEGG enrichment analyses, we found 143 GO items for pHThese GO terms and KEGG pathways were mostly associated with the regulation of the processes of protein modification, the activity of protein dimerization, hydrolase activity and the calcium signaling pathway; for details, see +, and the H+ accumulates in the body, which reduces the pH [+ during glycolysis, so the content of lactic acid can reflect the muscle’s pH.After slaughter, the blood circulation of sheep becomes stagnant, and the oxygen supply was insufficient. In this case, phosphocreatine phosphorylates ADP into ATP under the catalysis of phosphokinase to maintain the ATP level of the muscle cells . Then, gs the pH ,35. Pyru45min to pH72h, which was basically the same as the change in post-slaughter pH reported for other reported livestock and poultry [In this study, the mean value showed a downward trend from pH poultry ,30,36. H poultry  showed i poultry ,39. Post poultry ,41.45min with pH24h to pH72h, which may be because glycolysis of the muscle had not started 45 min after slaughter, while pH45min was related to the physiological status of the animals before slaughter [In this study, the pH at 45 min, 24 h, 48 h and 72 h after slaughter was determined. In the correlation analysis of pH at different time periods, there was no correlation of pHlaughter .24h, pH48h and pH72h, which might be related to the activation of AMPK and glycolysis of the muscle after slaughter with the same postmortem time and the same storage environment [There were significant positive correlations among pHironment ,43,44.The phenotype is the sum of the traits and characteristics exhibited by organisms under certain environmental conditions. Phenotypes are the result of a combination of the genotype and the environment. Genes and the environment are two main factors that affect biological traits. As internal and external factors, genes and the environment play their respective roles. Usually, biological traits are regulated by multiple genes, which are regulated by one or more pairs of genes in different formative periods. The genes interact with each other to affect the expression of traits.p) > 5, 28 significant loci were obtained, and the rate of phenotypic variation explained was 27.54–61.29%. In total, 36 genes were annotated from all loci. The rates of phenotypic variation explained at the significant sites were 32.59%, 27.54%, 44.52% and 61.29% for pH45min, pH24h, pH48h and pH72h, respectively, indicating that more phenotypic variation was explained. These characteristics were regulated by genes and influenced by the environment.In this study, based on the mixed linear model for single traits, GEMMA software was used to perform an association analysis for the pH traits. When the genomic significance criterion was −log10  was carried out on the two populations, and it was found that there was group stratification within the population, so the influence of group stratification should be considered in the analytical model. A mixed linear model of pH traits and phenotype values (MLM) was constructed, and a population stratification analysis was carried out using Q–Q plots. The results showed that the observed values and expected values were basically on a diagonal line, and the statistics of the observed values of significant SNP sites were above the expected values, indicating that the statistical distribution calculated by the SNP association analysis did not deviate from the hypothesis testing test. There was no group stratification in the population structure corrected by the kinship matrix, and the results of the mixed linear model of GEMMA were credible ,21.2 population of Texel sheep × Altay sheep, and 28 SNP loci reaching the level of genomic significance were detected. Among the detected SNPs, 13 SNPs were located within the genes, 13 SNPs were located between the genes, 1 SNP was located in the exon and 1 SNP was located in the ncRNA_UTR5. The main reason for this phenomenon is that according to the whole genome reference sequence information of sheep (Ovis_aries_v3.1), the 600 K chip of sheep that was selected was mainly based on the SNP data of major sheep breeds around the world and lacked SNP data from Chinese sheep breeds crossed with foreign sheep breeds. There were many problems, such as the lack of homogeneity of the loci and the lack of representativeness of the functional loci and regions. Combined with the data from the whole-genome resequencing analysis, the accuracy of the results of this experiment were improved compared with using the chip data alone.According to the phenotypic traits forming four different pH periods, a GWAS analysis was conducted on the F24h in the biological process category, which has four genes , the obsolete multi-organism process (GO:0051704) and the organonitrogen compound metabolic process (GO:1901564). The cellular component organization was a term (GO:0016043) of pH48h in the biological process category, which has six genes  and the cellular component organization or biogenesis (GO:0071840). The cell morphogenesis was a term (GO:0000902) of pH72h in the biological process category, which has three genes  and HILPDA and FAT1 were enriched in terms of cell-cell signaling (GO:0007267).The gene ontology enrichment analysis and KEGG pathways, in our study, revealed a number of GO terms and KEGG pathways. These involved significant genes related to the traits under examination; for example, the regulation of the protein modification process was a term (GO:0031399) of pHur genes . Among tix genes . Among tee genes . Among t24h (GO:0046983) in the molecular function category, which has four genes  and TGFB2 was enriched in terms of molecular function regulator activity (GO:0098772). The activity of hydrolase was a term of pH48h (GO:0016787) in the molecular function category, which has three genes  and the metal ion binding (GO:0046872). The cation binding was a term of pH72h (GO:0043169) in the molecular function category, which has one gene .The protein dimerization activity was a term of pHur genes . TGFB2 aee genes . MMP13 aone gene . FAT1 waThis above functional analysis suggested that some genes might be involved in the changes of muscle pH after slaughter through proteolytic degeneration ,46.24h were map00220: arginine biosynthesis, map00250: alanine aspartate and glutamate metabolism, and map00270: cysteine and methionine metabolism, all of which contain a GOT2 gene. The top three KEGG analysis pathways of pH48h were mapmap04657: IL-17 signaling pathway, map04926: relaxin signaling pathway, and map04928: parathyroid hormone synthesis secretion and action, all of which include MMP13 and MMP12 genes.The top three KEGG analysis pathways of pHThe functional analysis yielded many terms and pathways related to proteolytic activity, protein regulatory repair and the biological process. Therefore, it is reasonable to presume that all significant SNPs and candidate genes might be associated with pH.45min, pH24h, pH48h and pH72h ofthe longissimus dorsi muscle were detected, which were located on chromosomes 1, 2, 3, 4, 6, 8, 12, 13, 14, 15, 16, 17, 18, 20, 23, 25 and 26. Three SNPs were significantly correlated with pH24h, pH48h and pH72h, and all of them were located on chromosome 3.Through the genome-wide association analysis, the SNP loci significantly associated with pH45min was located in the 5 ‘UTR region of the non-coding RNA of CCDC92. CCDC92 is a coiled-coil domain protein, and a member of the coiled coil domain protein family, which mainly includes structural proteins, regulatory proteins, enzymes, regulatory factors, etc. A common feature of CCDC proteins is that they contain a curly helix domain with a superhelix structure formed by two to five helices encircling each other. The curly helix domain of the CCDC protein was used for many purposes, which enables the protein to have various functions [CCDC92 was an unknown molecular substance that affects adipocyte differentiation [CCDC92 affects the expression of fat genes, thus impairing adipogenesis, reducing peripheral fat storage and increasing the risk of heart disease. Klarin et al. [CCDC92 was significantly correlated with body fat percentage, and triglyceride and adiponectin levels, and a correlation was found with lipid metabolism disorders.According to the genomic location of SNP loci associated with a significant trait, the significant loci were annotated by ANNOVAR software. One SNP OAR17_51353307) located on chromosome 17 among the SNPs significantly correlated with pHunctions ,48. It hntiation . Lotta entiation  showed t353307 loCCDC92 may regulate the process of fat metabolism in the muscle and affect the muscle’s pH45min. Therefore, it was speculated that CCDC92 can be used as a candidate gene to affect pH45min.Based on the results of the above literature, 24h and were all located on the intron of KDM4C. KDM4C  was also known as GASC1 (Gene amplified in squamous cell carcinoma 1) or JMJD2C (Jumonji domain containing 2C). KDM4C was a histone demethylase belonging to the histone lysine demethylase (KDM) family. Larson et al. [KDM4C to counter-increase G9a (histone 3 lysine 9 dimethyltransferase) induced by the HF diet after birth, and the increased expression of the G9a protein reduced the number of beige fat cells (BA). In their study, Zhang et al. [TNFAIP3, KDM4C, HSPG2, BMP2, PLCB4 and GRM5 were candidate genes related to the body weight and body shape of pigs.Two SNPs (OAR2_74191733 and OAR2_74212523), which were located on chromosome 2, were among the SNPs significantly correlated with pHg et al.  used GEMTGFB2. TGFB2 was a subunit of transforming the growth factor-β (TGF-β), which has a certain influence on the growth and development of muscle. TGF-β was a superfamily of proteins that play an important role in the regulation of cell growth [TGF-β has a widespread influence on regulating the growth, development and body composition of chickens. Ueda et al. [TGF-β was a growth factor that can induce the secretion of COL4A in connective tissue. Compared with subcutaneous adipose tissue, the expression of TGFB2 and TGFB3 was higher in intramuscular adipose tissue, while the expression of TGFB1 was lower. In addition, an affymetrix microarray was used to analyze the gene expression profiles of abdominal adipose tissue of diabetic (GK) and control (WKY) rats. An important gene that was highly expressed in GK rats was the transforming growth factor β2 (TGFB2) [TGFb2 inhibited lipogenesis [Two SNPs (OAR12_20003596 and OAR12_20013208) located on chromosome 12 were all located on the intron of l growth  and diffl growth . Li et al growth  found tha et al.  showed t (TGFB2) , and theGOT2 gene and was 46.92 kb away from the gene. GOT2  was a type of glutamic-oxaloacetic transaminase 2 (GOT) in eukaryotes and exists in the cell’s mitochondria. Studies have shown that GOT was involved in amino acid metabolism and the tricarboxylic acid cycle (TCA), and it plays a role in cell proliferation. Decreased GOT2 can inhibit cell proliferation and slow down the rate of glycolysis [A SNP (OAR14_25937544) located on chromosome 14 was close to the ycolysis .KDM4C and TGFB2 regulate muscle pH by affecting adipocyte and lipogenesis. The GOT2 gene affects muscle pH through its participation in muscle glycolysis, so the above three genes can be used as candidate genes to influence pH24h.In conclusion, 48h was located between MMP13 and MMP12. MMP13  was one of the important members of the matrix mettalloproteinases (MMPs) family, and its main function was to degrade the extracellular matrix. Smith et al. have shown that MMP13 was essential for muscle growth and regeneration [MMPs) played a key role in the remodeling of the extracellular matrix (ECM) during muscle regeneration. In the muscles of chronically injured muscular dystrophy mice (mdx mice), the expression of MMP13 and its protein levels were elevated, and in differentiated mouse myoblast C2C12 cells, the expression of MMP13 was most pronounced after fusion of the myoblasts and during the formation of the myotube, suggesting that MMP13 plays a major role in the migration of myoblasts.One SNP (OAR15_5271378) on chromosome 15 among the SNPs significantly correlated with pHneration . Lei et neration  found thMMP12 , also known as macrophage elastase, was secreted mainly by macrophages, monocytes and other inflammatory cells as a kind of endoprotease. MMP12 can decompose components of the extracellular matrix and vascular components. Meanwhile, MMP12 was closely related to adipose tissue. The literature has shown that MMP12 can promote fibrosis in the process of repairing muscle injuries in rats [MMP12 gene and protein in human skin and fibroblasts [MMP12 plays a key role in controlling the weight of APCMin/+ mice [DRP1 was positively correlated with the expression of FOXM1 and MMP12. Deletion of DRP1 affected aerobic glycolysis by down-regulating glycolysis genes, and the overexpression of MMP12 in cells with a deletion of DRP1 helped restore the consumption of glucose and the production of lactic acid. in rats ,64. Chunroblasts . Jing etn/+ mice . Huang en/+ mice  showed tMMP12 may affect muscle pH through the process of repairing muscle injuries and the glycolysis pathway. MMP13 may affect muscle pH through the processes of muscle growth and regeneration, so it was speculated that MMP12 and MMP13 may be candidate genes affecting pH48h.In line with the results of the literature shown, it was found that 72h, a SNP (OAR4_92689824) located on chromosome 4 was adjacent to the gene HILPDA, 17.22 kb away from this gene. HILPDA  is also known as C7orf68, HIG-2 and HIG2. Proliferator-activated receptors (PPARs) were the target of peroxisome proliferators, which participate in the secretion of triglycerides and regulate the metabolism of fat in the liver [HILPDA regulates the cellular metabolism of lipids [Among the SNPs significantly correlated with pHP OAR4_929824 locaf lipids ,70,71, cf lipids .FAT1. FAT1  is a member of the fat cadherin superfamily and is a transmembrane protein of about 500 kDa, which has the functions of regulating the dynamics of actin, intercellular adhesion, cell polarity, etc. FAT1 is a group of transmembrane proteins commonly expressed in the epithelial tissues, with functions in adhesion molecules and/or signal transduction receptors [FAT1 can reduce the stability of cell connections and destroy the cells’ polarity [IDH2) on the homeostasis of the energy of skeletal muscles and showed that the expression levels of adipogenic pathway genes  were downregulated in IDH2 knockout (KO) mice. Meanwhile, mitochondrial NADP+-dependent isocitrate dehydrogenase (IDH2) catalyzes the oxidative decarboxylation of isocitrate to α-ketoglutaric acid and the reduction of NADP+ to NADPH. IDH2 acts as a metabolic regulator in the tricarboxylic acid cycle (TCA) by catalyzing the conversion of alpha-ketoglutaric acid, and as a major REDOX regulator through the production of NADPH.A SNP (OAR26_15183899) located on chromosome 26 was located in the exon region of eceptors ,75. The polarity . Lai et polarity . Pan et polarity  studied HILPDA may affect muscle pH through regulating the metabolism of fat. FAT1 may affect muscle pH through the fatty acid metabolism pathway and through participating in the process of adipogenesis, etc. Therefore, HILPDA and FAT1 are speculated to be candidate genes affecting pH72h.According to the results from the literature presented above, it was found that In this study, GWAS was used to preliminarily screen candidate genes related to the pH of sheep meat. To determine the functions of potential candidate genes or loci, functional verification of the cells and populations should be further conducted by molecular biological methods, so as to determine the influence of the candidate genes or loci on the traits of meat quality, to better guide the improvement of local breeding resources.2 population of Texel sheep × Altay sheep at different time periods, 28 SNPs were identified by GWAS. Finally, CCDC92 was identified as the candidate gene for pH45min, KDM4C, TGFB2 and GOT2 as the candidate genes for pH24h, MMP12 and MMP13 as the candidate genes for pH48h, and HILPDA and FAT1 as the candidate genes for pH72h. The main processes of the above genes were identified, namely protein modification and hydrolase activity. Our findings provide useful information for understanding the changes in the pH of mutton after slaughter and the storage/shelf life of meat, and they provide a new research direction for improving the storage time and meat quality of mutton.According to four phenotypic traits of pH in the F


Mycobacterium tuberculosis complex (MTBC) strains; however, the clonal expansion of one strain often limits its application in local MTBC outbreaks. The use of an alternative reference genome and the inclusion of repetitive regions in the analysis could potentially increase the resolution, but the added value has not yet been defined. Here, we leveraged short and long WGS read data of a previously reported MTBC outbreak in the Colombian Amazon Region to analyze possible transmission chains among 74 patients in the indigenous setting of Puerto Nariño (March to October 2016). In total, 90.5% (67/74) of the patients were infected with one distinct MTBC strain belonging to lineage 4.3.3. Employing a reference genome from an outbreak strain and highly confident single nucleotide polymorphisms (SNPs) in repetitive genomic regions, e.g., the proline-glutamic acid/proline-proline-glutamic-acid (PE/PPE) gene family, increased the phylogenetic resolution compared to a classical H37Rv reference mapping approach. Specifically, the number of differentiating SNPs increased from 890 to 1,094, which resulted in a more granular transmission network as judged by an increasing number of individual nodes in a maximum parsimony tree, i.e., 5 versus 9 nodes. We also found in 29.9% (20/67) of the outbreak isolates, heterogenous alleles at phylogenetically informative sites, suggesting that these patients are infected with more than one clone. In conclusion, customized SNP calling thresholds and employment of a local reference genome for a mapping approach can improve the phylogenetic resolution in highly clonal MTBC populations and help elucidate within-host MTBC diversity.Whole genome sequencing (WGS) has become the main tool for studying the transmission of IMPORTANCE The Colombian Amazon around Puerto Nariño has a high tuberculosis burden with a prevalence of 1,267/100,000 people in 2016. Recently, an outbreak of Mycobacterium tuberculosis complex (MTBC) bacteria among the indigenous populations was identified with classical MTBC genotyping methods. Here, we employed a whole-genome sequencing-based outbreak investigation in order to improve the phylogenetic resolution and gain new insights into the transmission dynamics in this remote Colombian Amazon Region. The inclusion of well-supported single nucleotide polymorphisms in repetitive regions and a de novo-assembled local reference genome provided a more granular picture of the circulating outbreak strain and revealed new transmission chains. Multiple patients from different settlements were possibly infected with at least two different clones in this high-incidence setting. Thus, our results have the potential to improve molecular surveillance studies in other high-burden settings, especially regions with few clonal multidrug-resistant (MDR) MTBC lineages/clades. Tuberculosis (TB) is one of the leading contagious diseases worldwide, with an estimated 10 million cases in 2020, 3% of which were in Latin America (LATAM) 13. In ColIn recent years, TB incidence in the WHO/Pan American Health Organization (PAHO) region of the Americas has been on the rise , especiaTo advance faster in the control and elimination of the disease in these vulnerable populations, the World Health Organization (WHO) has endorsed whole-genome sequencing (WGS) as a tool for understanding local epidemics to enable better public health interventions , 13. WGS14–To better understand the spread of an MTBC outbreak that occurred in 2016 among 23 indigenous settlements of the Ticuna, Cocama, and Yagua ethnicities in the remote setting of Puerto Nariño, in the Colombian Amazon Region , we perfThe TB outbreak comprised 80 positive cases out of 6,310 individuals screened from March to October 2016 , from whInitially, we defined the genotypes of all 74 isolates with 24-loci mycobacterial interspersed repetitive-unit–variable-number tandem-repeat (MIRU-VNTR) typing. The MTBC population structure was found to be highly homogeneous; 74/74 (100%) of the isolates belonged to the Euro American lineage, also known as lineage 4 (L4), 72/74 of which (97.2%) were Latin American Mediterranean (LAM), and 2/74 (2.7%) were identified as the Haarlem genotype. Of the LAM isolates, 31/72 (43.05%) and 41/72 (56.94%) were from indigenous settlements based on the Amazon and Loretoyaco Rivers, respectively . One large cluster comprised 49 patients with identical 24-loci MIRU-VNTR patterns, including 16 children. A smaller cluster was observed with 11 patients and 2 alleles distances. Patients in both clusters originated from different settlements in the study region, and 8/74 (10.8%) isolates had mixed MIRU-VNTR alleles .WGS was successfully performed for all 74 MTBC isolates. Phylogenetic classification of the isolates based on specific single nucleotide polymorphism (SNP) signatures described previously by Coll et al. classified them into 72 LAM sublineage 4.3.3., and two Haarlem sublineage 4.1.2.1 isolates  Table S. FurtherThe largest cluster, cluster I, contained 42 identical  isolates and 7 isolates differing by a maximum of two SNPs . Out of rpoB Ser450Leu (99.64%), katG Ser315Thr (100%), pncA His82Asp (99.68%), embB Met306lle (100%), and rpsL Lys88Thr (100%) conferring resistance to rifampicin, isoniazid, pyrazinamide, ethambutol, and streptomycin, respectively (rpoB Ser431Thr (6.62%) and rpsA Thr210Ala (8.21%) in COL-18, and rpsA Thr5Ala (10.57%) in COL-3.Molecular drug resistance prediction detected multidrug resistance in one LAM/4.3.3 isolate from a child (COL-74), which had mutations mediating resistance to all first-line drugs. Although this case was identified by contact tracing, it was not in a molecular cluster . The resectively . In addiRv1194c Trp244Arg, Rv3621c (PPE65) Gln253Arg, Rv3478 (PPE60), Rv3478 (PPE60) Ala326Ala, and Rv1945 Ala327Ala.In a first attempt to increase genotyping resolution, we explored whether the inclusion of SNPs in repetitive and resistance-associated genes increases the typing resolution for the outbreak. This approach improved the phylogenetic resolution and led to a subdivision of the largest cluster, cluster I . Overallde novo and used it as a reference genome. The COL-2 genome comprised 4,402,676 nucleotides  and was slightly smaller than the H37Rv reference genome with 4,411,532 nucleotides  based on the allele frequencies of 16 SNPs, differentiating especially cluster I, node G (5 SNPs), and cluster II (11 SNPs) isolates  were from Puerto Nariño and nearby settlements such as San Francisco, Ticoya, Veinte de Julio, and Puerto Esperanza, which is the main gathering area  and is located the Amazon River port that connects the indigenous settlements with the modern world.The classical MTBC genomic analysis indeed did not provide a significantly higher resolution than the 24-loci MIRU-VNTR genotyping investigation in our study setting. Here, only an extended variant calling approach could further increase the resolution of this outbreak scenario and identify new yet unrecognized transmission chains. First, we included repetitive regions such as proline-glutamic acid/proline-proline-glutamic-acid (PE/PPE) and resistance-associated genes in our analysis. Of note, PPE/PE genes account for nearly 10% of the genes of MTBC and might play a role in the virulence mechanisms of host-pathogen interaction , 29; howSecond, we assembled a new reference genome from an outbreak isolate of the largest node, node A, using long-read sequencing data. Molecular epidemiological approaches in recent years mostly have used H37Rv as a mapping reference. However, its use as a sole reference genome has been discussed, as this does not consider the genetic diversity across all 9 distinct human-adapted MTBC lineages and sublineages , 34. ThuWith this new resolution, we also found evidence that multiple patients are potentially infected with more than one outbreak strain. Others, however, have found considerable intrapatient heterogeneity, often related to one infecting clone . Previou37–Our study has limitations, such as the short study duration, rendering the comprehensive analysis of the TB epidemiology in the study region difficult. Future work should be based on longitudinal sampling enabling prospective molecular surveillance and allowing us to trace the evolution of drug resistance in locally dominating clades/strains. Our analysis was focused on SNPs, and the inclusion of insertions and deletions could further improve the phylogenetic resolution.Conclusions. In conclusion, we confirmed that the TB epidemiology in the indigenous setting of Puerto Nariño in the Southwest Colombian Amazon is mainly driven by the ongoing transmission of one outbreak strain. Almost one-third of the patients were possibly infected with at least two clones of the local outbreak strain, highlighting the need for interventions to break transmission chains and better TB control in the population. We also demonstrated that customized variant calling pipelines and a new local reference genome can moderately increase the resolution of MTBC outbreaks. The potential benefit of these customized reference-mapping approaches for molecular surveillance studies needs to be investigated in other outbreaks and may vary depending on the strain genetic background.We recovered a total of 74 MTBC isolates from primary sputum samples on Löwenstein-Jensen medium (LJ) from March to October 2016. These samples were obtained from patients with pulmonary TB allocated to 16 indigenous settlements based on the shore of the Amazon (AR) and Loretoyaco Rivers (LR) in Puerto Nariño . The socWe calculated descriptive statistics of the demographic data of the population studied, including proportions and median and interquartile ranges using the functions of base R and RStudio .plus (https://www.miru-vntrplus.org/MIRU/index.faces). Phylogenetic analyses were performed with BioNumerics software version 7.6 (Applied Maths). MIRU clusters comprised nodes with more than one isolate with an identical genotype. A 24-loci MIRU-VNTR dendrogram was calculated using the categorical distance and the unweighted pair group method with an arithmetic mean algorithm (UPGMA).We extracted genomic DNA using the PureLink genomic DNA minikit (Thermo Fisher Scientific) according to the manufacturer’s instructions. DNA samples were genotyped using 24-loci mycobacterial interspersed repetitive-unit–variable-number tandem-repeat (MIRU-VNTR) as follows. Multiplex PCR amplification was performed with a GenoScreen typing kit, and fragment separation was run on the ABI 3500XL automated sequencer as described previously . FragmenMycobacterium tuberculosis H37Rv (GenBank ID NC_000962.3) using the Burrows-Wheeler Aligner Alignment tool  according to the manufacturer’s instructions . We analent tool , and refCluster analysis was performed using the MTBseq pipeline with a threshold of 5 SNPs , 52.De novo genome assembly was performed using the PacBio SMRTlink software version 9.0 and its microbial assembly application, with the genome length set to 4.4 Mb and a seed coverage of 30. The assembly of 54,267 subreads  resulted in two polished contiguous sequences (contigs) of 3,947,682 and 454,994 bp, respectively.A new reference genome of one outbreak strain named COL-2 was assembled using the Single Molecule Real Time (SMRT), long-read technology of the Sequel II system (Pacific Biosciences [PacBio]) to increase the resolution of the outbreak. We selected the local isolate COL-2 from the largest clonal cluster to serve as our reference. The DNA library was prepared with the SMRTbell Express Template prep kit version 2.0 with barcoded adapters from Integrated DNA Technologies (IDT) and sequenced on the Sequel II system. Maximum parsimony trees (MPT) were generated with BioNumerics either based on a distance matrix derived from the standard 24-loci MIRU-VNTR data or derived from the three reference-mapping approaches based on a concatenated SNP alignment with classical SNP calling thresholds: (i) the classical comparative MTBC genomic pipeline, (ii) including repetitive regions and drug resistance-associated regions, and (iii) reference mapping to a new outbreak genome and including repetitive regions. All approaches employed the default MTBseq conservative SNP-calling parameters described above. In the data sets, the sample ID number is preceded by the label COL- which refers to Colombia; however, only the ID number is depicted on the MPT.n = 67) for variants with variable allele frequencies in 16 outbreak-differentiating SNP positions using binoSNP as well as in resistance-associated regions   files of the outbreak isolates (sidered) . The 16 NC_000962.3)  (GenBank ID 00962.3) –56 and P0962.3) – with Gen0962.3) –. Repetithttps://www.datos.gov.co.The geographical maps shown are an adaptation of Google and Colombian National Maps: Comunidades Indígenas de Puerto Nariño and Asociación de Indígenas, Tikuna, Cocama and Yagua (ATICOYA). Open data were provided by Gobernación del Amazonas at PRJEB57971 and PRJEB57950 (see Table S1).The Illumina short-read sequences of the 74 genomes of the outbreak and the PacBio long-read sequence corresponding to the local reference genome COL-2 are publicly accessible in the European Nucleotide Archive under the projects


In Ethiopia, fruits pose a significant production and marketing challenge for farm households that significantly affect their farm profitability due to their perishability and unpredictable seasonal pricing. For instance, seasonally, market prices vary depending on the quality and quantity of fruit products available on the market. Stemming from this logical ground, this study is initiated with the objective of characterizing production systems and market performance of fruits in Ethiopia, focusing on apple and mango crops.A random sampling approach was used for producers and snowball sampling for traders when selecting survey participants. A pre-tested survey questionnaire was used for data collection. Descriptive statistics and market margins were used for statistical analysis.Post-harvest wastage is preventing farmers from receiving anticipated revenue, implying that approximately 31.8 and 26.1% of the total mango and apple produce was lost, respectively. According to the survey results, there was no measurement consistency among farmers, local collectors, and small retailers. District level collectors received a higher margin share  than other actors in the chain, which was unjustified given their contribution to the market chain. Farmers were comparatively hampered by the market since they earned the lowest share  of consumer prices indicating that the apple and mango market chain performance is poor. As a consequence, these all deter farmers from producing in large quantities, quality, and also uncertainty (fair failure in the mind of farmers) in the marketing of apples and mangoes.The awareness of small-scale farmers about most of the agronomic practices including insect pests and diseases were very low. Hence, this study recommended that there is an urgent need from district agricultural offices to improve mango and apple production and marketing systems in the study districts. In developing countries, the share of high-value agri-food products such as fruits and vegetables is rapidly increasing in consumers’ diets  is regarded as “the king of fruits”, making the crop valuable for ensuring food security, especially in emerging nations where this issue is still present  production accounts for more than half of the world’s deciduous fruit tree farming. In 2018/2019, about 86 million tons of apple was produced worldwide  in four districts. A multi-stage sampling technique was used to sample farm household heads, which included both purposive and random sampling methods. Firstly, four districts  were purposively chosen. These districts were selected in order to capture socioeconomic situations, agro-climate zone differences, and fruit producing experiences. Secondly, ten sample kebeles were randomly selected. Finally, utilizing the Mugenda and Mugenda  table, aChagni, Dibatie, Bahir Dar and Enjibara) were selected as the main apple and mango marketing sites for the study areas. Due to the lack of a recorded list of the population of traders in this situation and the traders' opportunistic behavior, sampling is a particularly challenging task. Therefore, a snowball sampling technique  increases and vice versa. It also provides a measure of how benefits are allocated among the producers and marketers.Growing fruit crops like apple and mango under a variety of agro-climatic conditions can be very profitable and competitive, as well as offer opportunities in the current study. Unfortunately, small-scale mango and apple growers have not taken advantage of these prospects due to poor market pricing for their product and the high expense of post-harvest losses. For instance, post-harvest wastage inhibits farmers from earning the money they anticipated and shows that 31.8 percent of the entire mango production was lost. According to empirical studies, post-harvest losses in fruit are estimated to be 20–40% in underdeveloped nations and 5–20% in developed nations Mashav . Most peAccording to the descriptive result, depicted in Fig. Furthermore, there are farmers in apple-growing districts that have high levels of productivity. The Banja district's total productivity exceeds that of Fagita Lekoma. This could be due to the right use of common farming techniques including fencing, thinning and pruning, composting, manure, pest control, and others. Apple producers are also being hampered by post-harvest wastage, with estimates indicating that 26.1 percent of total apple production was lost Fig. b. OveralTable According to field observations, the two most prevalent fungal diseases of mango in the research locations are “powdery mildew” and “anthracnose.” Apple scab, twig blight powdery mildew, and mildew are among the most common diseases that have reduced apple yield and productivity. Farmers spraying pesticide chemicals . Insect pests that harm apple productivity include aphids, caterpillars, and scale borer.In terms of fertilizer use, no apple or mango farmers used inorganic fertilizer  on fruit-growing land, whereas the majority of farmers used organic fertilizer . Figure The primary cultivars grown in the study area include Kent, and Tommy Atkins. According to the study, the district office of agriculture, non-governmental organizations , and private seedling suppliers are currently the main seedling supply sources. According to Fig. In Ethiopia, the district-level marketplace is a well-known trading hub for a wide range of agricultural products. Nevertheless, the vast majority of economic agents exchange agricultural products in local markets using multiple, non-uniform units of measurement. The local units of measurement for fruits range from volumetric  to weight measures (sack) and weight balance (kilogram) and counting. Overall, measurement system heterogeneity leads to significant measurement costs, market disintegration, and exchange inequitably  for apple production and moving to the different terminal markets. These are:Due to the consistency and product quality aspect of the product, wholesalers are not willing to purchase apples. The marketing channel for apples is short because of this. A total of 138.15 quintals of apples were sold by farm respondents during the study year. About 81% of the overall volume sold by farmers passes via channel III (Farmers ⇒Collectors ⇒Retailers ⇒Consumers) with the largest share. This suggests that channel three is also more efficient at distributing large amounts of sales. This simply proves that a collector-created link was preferred in terms of absorbing a huge amount of apple products. The lowest apple quantity (7%) passes across channel I (Farmers ⇒Consumers). Unlike this result,  for mango production and moving to the different terminal markets. These are:The lowest mango quantity (1.03%) passes across channel seven . About 50.55% of the overall volume sold by farmers passes via channel six with the largest share. This implies that channel 6 is more effective in terms of distributing large amount of mango sales. Kassa et al.  identifiParallel to channel surveys, margin analysis can be performed and helps to assess how pro-poor or superior a market chain is. The marketing margins for apples and mango were determined as followed by taking the estimated sales prices of the respective actors in the market chain . The findings in Tables The structure of selling prices, margins, and price shares in each of the chain divisions is presented in Table With regard to mango, local collectors take the highest 40.18%) in terms of margin share, followed by wholesalers (19.30%). Margin analysis showed that about 84.92% of the chain’s gross marketing margin belongs to mango traders, while farmers receive approximately 15.08% of the gross marketing margin. That is, while farmers doing all the work of producing the mango crop and bearing the associated risks, took only 15.08% of the benefit share  in the marketing of apples and mangoes.Pawe and Adet should play a key role in identifying disease-resistant and high-yielding cultivars with the goal of enhancing apple and mango production.Based on the findings of this study, the following are potential areas of intervention for the agriculture offices as well as other development practitioners, who are going to support the fruits (apple and mango) production and marketing in the study districts. Apple and mango productivity in the study area is low, implying a higher effort requirement in supporting small-scale producers in terms of training and advice on the agronomic practice of apple and mango production. Train farmers about land preparation, planting, weed control, fruit management, compost preparation, soil moisture control, and post-harvest handling to boost apple and mango production and productivity is essential. Besides, the greater price disparity between farmers and intermediaries/traders indicates that farmers received little assistance. Therefore, establishment of fruits marketing cooperative is required in the study areas to strengthen farmers bargaining power. In line with this, empowering of small-scale farmers to be engaged in vertical and/or horizontal integration is quite important for the efficient use of apple and mango farming and maximizing household’s income. Furthermore, encouragement of farmers to use calibrated weight balances when selling apple and mango produce is required. To reduce cheating on weight balance, development agents should advise farmers on how to properly implement these measurement tools for apple and mango produce marketing. More importantly, agricultural research institutes such as


Zm00001d026568 and Zm00001d026569 were highly associated with SNP 2376873-7-G and encoded pentatricopeptide repeat-containing protein and chloroplastic palmitoyl-acyl carrier protein thioesterase, respectively. As expected, higher expression levels of these two genes are associated with higher chlorophyll contents. These results provide a certain experimental basis for discovering the candidate genes of chlorophyll content and finally provide new insights for cultivating high-yield and excellent maize suitable for planting environment.Chlorophyll is an essential component that captures light energy to drive photosynthesis. Chlorophyll content can affect photosynthetic activity and thus yield. Therefore, mining candidate genes of chlorophyll content will help increase maize production. Here, we performed a genome-wide association study (GWAS) on chlorophyll content and its dynamic changes in 378 maize inbred lines with extensive natural variation. Our phenotypic assessment showed that chlorophyll content and its dynamic changes were natural variations with a moderate genetic level of 0.66/0.67. A total of 19 single-nucleotide polymorphisms (SNPs) were found associated with 76 candidate genes, of which one SNP, 2376873-7-G, co-localized in chlorophyll content and area under the chlorophyll content curve (AUCCC).  Zea mays L.) is an important source used for animal feed and bioenergy and has become the top crop produced in China, with production estimated up to 272.6 million tons (MT) in 2021 . High yield based on photosynthesis has always been the focus topic in crop breeding [Maize  of chlorophyll content in leaves of different populations of various crops from different angles and have made considerable progress ,17,18,19to aging . HoweverZmVPP1, and transgenic maize with enhanced ZmVPP1 expression exhibited improved drought tolerance. Sun et al. [As a research tool, GWAS have become a common way to study natural variation and inheritance of important agronomic traits in various plants . Maize hn et al.  identifin et al.  used GWAIn this study, 378 maize inbred lines and 96,726 SNPs were used for the GWAS of the chlorophyll content in two environments. The purpose of this study is to identify candidate genes of chlorophyll content. Our findings provide new insights for mining candidate genes of leaf chlorophyll content.An association panel comprising 378 diverse maize inbred lines from the northeast of China, temperate region in the United States and the International Maize and Wheat Improvement Center (CIMMYT), Mexico, were used for GWAS. All materials were kept in the College of Bioscience and Biotechnology, Shenyang Agricultural University.n is the number of assessment times, γ is the meter reading, i is the ith rating date, and t is time (in days).The 378 inbred lines were grown in Fushun City, Liaoning Province, China  in May 2017 (17FS) and Ledong city, Hainan Province, China  in November 2017 (17LD). The field experiment was designed as random blocks with 2 replicates. Fifteen plants were planted in a 2.5 m long row with 0.6 m row distance, and the planting density was approximately 45,000 plants/ha. The inbred lines were labeled before pollination for standard field management. Chlorophyll content was measured using a portable chlorophyll meter , which was non-destructive, fast and cheap. SPAD-502 readings were taken from five plants per plot on five dates at a 5 d interval starting 0 d after silking. There were three measurements in the middle of the ear leaf for each plant, and the average value was used for the statistical analysis. AUCCC was calculated based on SPAD-502 readings on all measure dates. Larger AUCCC values represent higher chlorophyll content, and lower AUCCC values represent lower chlorophyll content. The formula used to calculate AUCCC was modified from the AUCCC formula :AUCCC = l + rk(l) + fi + (fe)il + εlikyijk = μ+e, where yijk was the phenotypic value of the attenuation rate ijk in this test, μ denoted the average value of attenuation rate, el was the influence of two environments, rk(l) was the repeated effect in the environment, fl was the genetic effect of the ith family, (fe)il was the interaction between genetic and environmental effects, and εlik was a random error.The “PROC MIXED” program in SAS software was used to analyze the variance heritability of the phenotypic values at the two places. The mixed linear model (MLM) was used for the analysis, and the model 2 = σg2/(σg2 + σge2/e + σε2/re)h [2h represents the generalized heritability of the trait, 2σg is the genetic variance of the trait, 2σge represents the variance of the interaction between genetic and environmental effects, 2σε denotes the residual error, and e and r denote the number of environments and the number of repetitions of the trait in each environment. The total phenotype of the two trials was predicted and expressed by the best linear unbiased prediction (BLUP) value so as to minimize the environmental impact.The generalized heritability formula is:  σε2/re) , where hp value was calculated as 1/n , and we obtained p < 1.03 × 10−5 as significant nodes.The 96,726 SNPs (MAF ≥ 0.05) were used to conduct GWAS by combining the data from two genotyping platforms (RNA-seq and SNP array). The mixed linear model (MLM) calculation method was used to analyze the association of chlorophyll content in R 4.0.3, where population structure and kinship were fitted to control false positives ,33. We u2 < 0.2). The physical locations of significant SNPs were determined using the B73 RefGen v4 database. The annotated genes were searched within the 100 kb region around (50 kb upstream and 50 kb downstream) the detected significant SNP and were identified based on functional domains. The function of annotation genes referred to the MaizeGDB (https://maizegdb.org/), NCBI (https://www.ncbi.nlm.nih.gov/gene) and the homologous genes of Arabidopsis.The most significant SNP was selected to represent the locus associated with chlorophyll content in the same LD block  method [ZmTubulin1 (Zm00001d033850) was used as an internal control for data normalization. All data were measured in three independent biological replicates. The primers are listed in The SNP allele effect was analyzed using R 4.0.3, and leaves of 6 varieties  were selected during maize V4 stage. A leaf segment of 2 cm in length was excised from the middle of the fourth leaf and stored at −80 °C. The RNAprep Pure Plant Kit was used to extract the RNA (TIANGEN). cDNA was synthesized from 2 μg of total RNA using the FastKing RT Kit (TIANGEN). RT-qPCR reactions were performed using a Bio-Rad  real-time PCR system using the SuperReal PreMix Plue (SYBR Green) (TIANGEN). Transcript levels were analyzed using the comparative CT  were calculated between chlorophyll content of ear leaf and 10 agronomic traits, including hundred kernel weight (HKW), flowering time (FT), ear rows number (ERN), kernel number per row (KNR), ear length (EL), ear perimeter (EP), kernel length (KL), kernel width (KW), kernel thickness (KT) and kernel area (KA). As shown in p < 1.03 × 10−5 , chloroplastic palmitoyl-acyl carrier protein thioesterase and UDP-D-galacturonate, respectively , gradually increased after pollinating. AAP belongs to the amino acid/auxin permease family, which is involved in transportation of the principal nitrogen assimilates amino acid [AAP2 gene was mutated in Arabidopsis thaliana, the mutant leaf had more chlorophyll content than the wild-type plant [Zm00001d003403 expression in maize. These results are in line with previous reports.Expression of ino acid ,40. Whenpe plant . The leaZm00001d026568 and Zm00001d026569 genes were associated with the same SNP 2376873-7-G. The relative expressions of Zm00001d026568 and Zm00001d026569 were higher in the genotypes carrying the SNP A allele  families in plants that is involved in biotic/abiotic stress, compound storage and plant growth and development [A total of 76 candidate genes were identified for the chlorophyll content and the dynamic changes of chlorophyll content according to the position of significantly associated SNPs. In addition, Li et al. , which ielopment ,74,75,76elopment ,78. Palmelopment . Fatty aelopment ,81. Leafelopment ,83. TherZm00001d026563, Zm00001d026569, Zm00001d026568 or this SNP may help to regulate chlorophyll content in maize breeding. Taken together, the discovery of candidate genes provides help for further analyzing the molecular regulatory network of chlorophyll content on maize ear leaves. The identification of SNP will promote marker-assisted selection in maize molecular breeding.To explore the potential roles of candidate genes in regulating chlorophyll content, we performed expression profiling analysis on RNA-seq data from different tissues at 0, 6, 12, 18, 24, and 30 days after pollination. The expressions of AP2/EREBP transcription factor 40 and chloroplast palmitoyl carrier protein thioesterase in leaves were low, and the expressions were moderately high on the 6th day after pollination. These results indicate that they have direct or indirect effects on chlorophyll content. Thus, selection of Zm00001d026568 and Zm00001d026569 contained significant SNP and encoded pentatricopeptide repeat-containing protein and chloroplastic palmitoyl-acyl carrier protein thioesterase, respectively. They were found to be highly expressed in lines with the A allele as determined by RT-qPCR. These candidate genes provide valuable resources for further study of the molecular network regulating chlorophyll content in maize. In addition, the prediction of SNPs with chlorophyll content may help devise effective breeding plans and selection strategies to improve maize yield.In this study, we discovered candidate genes of natural variation in maize ear chlorophyll content by GWAS. Chlorophyll content appeared to be of moderate heritability and showed extensive variation in the association panel, indicating that chlorophyll content is a quantitative trait suitable for GWAS. GWAS showed that the natural changes regulating chlorophyll content had manymicro effect loci. We found 19 SNPs containing 76 candidate genes that may participate in leaf senescence, photosynthesis, and plant developmental processes. One of the SNPs was co-localized in AUCCC and chlorophyll content that was associated with five genes.


Diospyros kaki Thunb., 2n = 6x = 90) collection in South Korea by evaluating 9751 genome-wide single-nucleotide polymorphisms (SNPs) detected using genotyping-by-sequencing in 93 cultivars. The results of neighbor-joining clustering, principal component analysis, and STRUCTURE analysis based on SNPs indicated clear separation between cultivar groups , pollination-constant astringent , pollination-variant nonastringent , and the pollination-variant astringent type ) based on the astringency types, while separation between PVA and PVNA-type cultivars was unclear. Population genetic diversity based on SNPs showed that the proportions of polymorphic SNPs within each group ranged from 99.01% (PVNA) to 94.08% (PVA), and the PVNA group exhibited the highest genetic diversity (He = 3.86 and uHe = 0.397). F (fixation index) values were low ranging from −0.024 (PVA) to 0.176 (PCA) with an average of 0.089, indicating a deficiency of heterozygosity. Analysis of molecular variance (AMOVA) and Fst among cultivar groups indicated that variation within individuals was higher than that among the groups. Pairwise Fst values among the groups ranged from 0.01566 (between PVA and PVNA) to 0.09416 (between PCA and PCNA), indicating a low level of cultivar type differentiation. These findings highlight the potential application of biallelic SNPs in population genetics studies of allopolyploids species and provide valuable insights that may have significant implications for breeding and cultivar identification in persimmon.This study investigated the genetic diversity and population structure of a persimmon ( Diospyros (family: Ebenaceae), which comprises approximately 400 plant species, are distributed in the tropical regions of Asia, Africa, and Central and South America. However, some species, such as Japanese persimmon, are distributed in temperate regions [Diospyros kaki Thunb.), ‘Goyum’ (Diospyros lotus L.), American persimmon (Diospyros virginiana L.), and ‘Youshi’ (Diospyros oleifera Cheng) [D. kaki, D. lotus, and D. oleifera are cultivated as fruit trees, whereas D. lotus and D. oleifera serve as sources of raw and dried fruits and persimmon oil (tannin), respectively [D. kaki and its relationship to other Diospyros species. Persimmon cultivation is believed to have begun more than 2000 years ago in China, which is known as a primary center of genetic origin. Then, it spread to Korea, Japan, and several European countries for centuries as an important fruit crop [Most members of the genus  regions ,2. Amonga Cheng) . In ChinD. kaki are hexaploid (2n = 6x = 90) and are alloploid with complete fertility [D. lotus L. and D. oleifera Cheng are diploids (2n = 2x = 30), while D. virginiana L exhibits two karyotypes (tetraploidy or hexaploidy) [D. oleifera’ is approximately 812.3 Mb (0.83 pg/1C) with 28,580 genes [D. oleifera is one of the ancestral species of allohexaploid cultivars [Diospyros lotus L.), a close wild relative of the oriental persimmon [Polyploidy is commonly observed in fruit tree species . Persimmoid 2n = x = 90 an80 genes ,8. D. olD. kaki Thunb. is classified into the following two cultivar groups based on the presence or absence of an astringent flavor in the fruits during harvest: sweet persimmon and astringent persimmon. Each group can be classified into variant and constant cultivar types depending on the relationship between the presence of seeds and flesh color. The flesh color of the variant type is affected by pollination. If seeds are produced as a result of pollination, the flesh color of the variant type is darker. Conversely, pollination or the presence of seeds does not affect the flesh color of the constant type. Therefore, the variant and constant types are referred to as pollination-variant and pollination-constant, respectively. Based on the effects of seeds on the astringent taste and deintercalation of mature fruits, persimmons can be astringent or nonastringent and are classified into the following four cultivar types: pollination-constant nonastringent (PCNA), pollination-constant astringent (PCA), pollination-variant nonastringent (PVNA), and pollination-variant astringent (PVA) [nt (PVA) ,10. Amonnt (PVA) , while ‘The genetic diversity and relationship of persimmons have been studied using molecular markers, such as random amplified polymorphic DNA (RAPD) ,13, amplThis study aimed to analyze the genetic diversity and population genetics of 93 cultivars at the SPRI based on large-scale SNPs identified using GBS.To identify genome-wide SNPs, 93 persimmon cultivars were subjected to GBS analysis . The GBSAn integrated SNP matrix was prepared using raw SNPs from 93 cultivars. The total number of observed SNPs was 236,947, ranging from 63,916 (‘Hongchoo’) to 9774 (‘Black Sweet Persimmon’), with an average of 44,804 per cultivar. SNPs that passed the filter criteria were classified as homozygous, heterozygous, or other types. The number of homozygous SNPs ranged from 7071 to 42,796 , while that of heterozygous SNPs ranged from 987 to 5614 (average: 4447). The remaining SNPs could not distinguish between types. After excluding SNPs that had a minor allele frequency (MAF) greater than 5%  and missing data greater than 30% , 9751 SNPs were selected . The genGenetic analyses of the population structure, principal component analysis, and hierarchical clustering were conducted for 93 persimmon cultivars comprising four cultivar types  using 9751 SNPs. Population structure analysis revealed that estimation of the delta K parameter inferred the most suitable model with five subpopulations (K = 5) a. The grHierarchical clustering using 9751 SNPs was performed to evaluate the genetic relationships among 93 cultivars. Two major clusters (I and II) were observed in the phylogenetic tree . In geneIn Cluster II, 51 cultivars were identified with the PCNA-type accounting for most of the cultivars (39 varieties). Cluster II can be divided into two subclusters. In Subcluster II-1, 35 of the 40 varieties were PCNA-type cultivars. ‘Uenishiwasw’ and ‘Sunami’ are bud mutations of ‘Matsumotowase-Fuyu’ and ‘Fuyu’, respectively, and these cultivars were closely located in Subcluster II-1. Similarly to Subcluster I-3, Subcluster II-2 comprised a mixture of 11 cultivars of four different types. The new Korean cultivar ‘Gamnuri’ (PCA), which is a processing cultivar obtained by crossing ‘Sunami’ (PCNA) with ‘Johongsi’ (PVNA), was classified into the same group as ‘Migamjosang’ (PVNA) and ‘12-9-4’ (PVNA). An unknown cultivar type, ‘11-6-120′, was located most closely to ‘Johongsi’ (PVNA) in Subcluster II-2.The clustering patterns indicated that cultivars originating from the same country tended to be closely grouped. Most Korean PCA-type cultivars were distinct from Japanese PCA-type cultivars. Japanese PVNA-type cultivars were clustered as an independent group from the Korean PVNA-type cultivars. For the PCNA-type, cultivars were closely related in two different countries. However, insufficient sample numbers limited the evaluation of European (two cultivars) and Chinese cultivars (four cultivars).Principal component analysis of 93 persimmon cultivars based on 9751 filtered SNPs  revealedGene diversity analysis of the SNP loci was performed on 91 cultivars except 2 cultivars with unknown astringency types. Based on the maximum number of SNPs allowed as input data for running the GenAlex software (v.6.50), 8095 out of 9751 SNPs were selected by filtering out the SNPs with high heterozygosity rates . In the The level of genetic diversity of the four cultivar types as subpopulations was calculated. The proportions of polymorphic SNPs within the PCA (19 cultivars), PCNA (40), PVA (9), and PVNA (23) groups were 98.85%, 97.58%, 94.08%, and 99.01%, respectively. MAF and polymorphic information content (PIC) values were in the range of 0.00−0.50 and 0.00−0.375, respectively, for all subpopulations based on the cultivar type . The disF (fixation index) values ranged from −0.024 (PVA) to 0.176 (PCA) among the cultivar groups with an average of 0.089, indicating a deficiency of heterozygosity in this persimmon collection (The mean Na of each cultivar group ranged from 1.941 (PVA) to 1.990 (PVNA) and was lower than 2.0, indicating that some SNP loci were monomorphic in all accessions for each cultivar group. For genetic diversity, the value of Ho ranged from 0.319 (PCA) to 0.337 (PVA) and was lower than that of He in all cultivar groups, except for PVA, in which He (0.361) was slightly lower than Ho (0.337). However, the PVNA group exhibited the highest genetic diversity (He = 3.86 and uHe = 0.397). llection .Fst among cultivar types (groups) , indicating low genetic variation among groups. These results indicate high genetic differentiation within the population.Genetic variation among the cultivars  was evaluated by performing an analysis of molecular variance (AMOVA) and calculating the (groups) . AMOVA rFst values among the groups ranged from 0.01566 to 0.09416, indicating a low level of cultivar type differentiation . The results of neighbor-joining clustering, principal components analysis, and STRUCTURE analysis indicated a clear separation between the Korean and Japanese cultivar groups and astringency types, especially between the PCNA and non-PCNA cultivars. AMOVA also revealed significant differences among astringency types. However, most molecular variations were detected among cultivars but not among cultivar groups based on astringency types, which indicates that the cultivar types were genetically similar at the molecular level with most polymorphisms being attributed to individual cultivar differences. Similarly, previous studies using SSR, AFLP, and RAPD have demonstrated differences among cultivars and population differentiation according to geographical origin and astringency type. Badness et al.  used RAPGenetic variation within a population of persimmons has also been demonstrated in other studies. Guan et al.  used 143The results of population genetic analysis based on SNPs in this study were similar to those of previous studies using various types of molecular markers. This indicates the reliability of using the biallelic SNP marker type in genetic studies on allopolyploids. The accuracy of genotyping in polyploids is lower than that in diploids when biallelic SNP genotyping techniques such as GBS are used due to their multi-locus alleles and multiallelic states at a single locus ,31. ThisIn conclusion, the study highlights the potential of genome-wide SNP analysis in evaluating genetic diversity and population structure of persimmon cultivars. The outcomes indicate a substantial degree of genetic diversity in the sample collection, with notable differentiation observed among astringency types and geographical regions. Nevertheless, the study finds that most of the genetic variation can be attributed to individual cultivars, suggesting a high level of genetic similarity among cultivar types at the molecular level. These findings are consistent with earlier studies that used different molecular markers, which confirms the robustness of SNP markers in genetic studies on allopolyploid species such as persimmons. The study provides valuable insights into the genetic diversity of persimmon cultivars, which could have significant implications for breeding and cultivar identification.Diospyros lotus L) (2n = 2x = 30), was used  maintained in the Persimmon Research Center, GNARC , were used as an accession panel for population genetic analysis based on SNPs. For EST-SSR marker development, a sample panel comprising 8 cultivars, including the diploid cultivar ‘Goyum’ (was used . Genomic−1) of each sample was used to prepare a set of PstI-MspI sequencing libraries according to the standard GBS library analysis method [The genomic DNA  and 200 U T4 DNA ligase was added to the restriction enzyme-treated fragments to attach the adapter-containing barcode and a common adapter, after which pooling was carried out for preparing 96 samples. After pooling, the suitability of the constructed libraries for GBS analysis was evaluated using gel electrophoresis. The prepared library was purified using the Qiagen MinElute column and sequenced using the paired-end sequencing method with Hiseq 2000. Raw GBS data were demultiplexed using the barcode sequences, and the barcode and adapter sequence were removed using the Cutadapt program (v.1.8.3) [http://persimmon.kazusa.or.jp, accessed on 10 May 2021) using the BWA (0.6.1-r104) program [SEEDERS in-house script [-Homozygous: SNP read depth ≥ 90%-Heterozygous: 40% ≤ SNP read depth ≤ 60%-Others: 20% ≤ read rate < 40% or 60% < read rate < 90%.The genomic DNA of each of the 93 samples was double-digested with v.1.8.3) . Then, sv.1.8.3) . Dynamic program , and a B program  under the script . The SNPSEEDERS in-house script. The genomic distribution of filtered SNPs was visualized using the basic plotting function of the Circos program [http://www.r-project.org/, accessed on 17 May 2021).Finally, SNP filtering was performed to select SNPs at a level suitable for subsequent analysis based on biallelic SNP loci, MAF of > 5%, and missing rate of < 30% by using the  program  in R verip2), Shannon’s information index (I = −1 Σ (ip × ln (ip)), uHe (uHe = (2N/(2N − 1) × He)), and fixation index (F = (He − Ho)/He), where N is the total number of individuals, pi is the frequency of the ith allele for the population, and Σ ip2 is the sum of the squared population allele frequencies. The PIC value was calculated using the following formula [n is number of marker alleles and ip and jp are the allele frequency in the populations i and j, respectively. The level and source of molecular genetic variation were analyzed using AMOVA with the GenAlex program.Genetic diversity analysis was performed using GenAlex program (v.6.50)  with the formula :(1)PIC=1The population structure of the 93 accessions was analyzed with the admixture-based model (Markov chain Monte Carlo-based Bayesian model) using the STRUCTURE program (v.2.3.4) ,49. The


Prevotella maculosa, Corynebacterium pyruviciproducens, and Mogibacterium timidum while it decreased Prevotella copri. Low‐fat cookie intake increased Cyanobacterium aponinum and Desulfovibrio butyratiphilus and reduced Alloscardovia omnicolens. There were no significant differences in circulating gut permeability protein  levels. There was a slight increase in the amount of bowel movement with mango consumption, but no significant findings for frequency, consistency, strain, pain, and constipation in bowel movement between trials. Given these results, it can be concluded that consumption of mango may have positive effects on the gut health, which may yield possible health benefits for chronic disease that deserve further study.Some individual fruits have been widely researched for their effects on overall health and correlations with chronic diseases. The beneficial effects of mango supplementation on metabolic diseases have been detected. However, research into mango consumption on gut health, including the microbiome, is limited to processed mango preparations or peels. Our goal was to examine the effects of fresh mango consumption on the gut microbiome, gut permeability proteins, and bowel movement habits in overweight/obese individuals. In a 12‐week crossover design study, 27 participants consumed 100 kcal/day of either mangos or low‐fat cookies with a washout period of 4 weeks. The mango intervention showed higher Shannon–Wiener and Simpson alpha diversity indices of the microbiome than the low‐fat cookie intervention in week 4. Significant differences in beta diversity of the microbiome were found between diet interventions at week 12. Mango consumption increased the abundance of  The objective of this study was to examine the effects of fresh mango consumption on the gut microbiome, gut permeability proteins, and bowel movement habits in overweight/obese individuals. In a 12‐week crossover design study, 27 participants consumed 100 kcal/day of either mangos or low‐fat cookies with a washout period of 4 weeks. This study suggests that consumption of mango may have positive effects on the gut health, which may yield possible health benefits for chronic disease that deserve further study. The gut microbiome has several functions within the body, including regulating the immune system and influencing chronic disease. For example, the gut microbiome regulates the homeostasis of cells in both the innate and adaptive immune systems Wu & Wu, . AdditioPrevotella to Bacteroide dominance , and fiber . DNA isolation and quantification, and 16 rRNA gene sequencing were performed at Laragen Inc.2.4g for 10 min at 4°C for serum separation. Serum samples were stored at −80°C. Human tight junction proteins, zonula occludens‐1 (ZO‐1), claudin‐2 (CLDN2), and occludin (OCLN) were measured using ELISA kits (MyBioSource).Participants were asked to fast 11–12 h prior to the collection of blood samples. Fasting blood samples were collected at baseline, week 4, and week 12 and centrifuged at 1200 2.5Bowel movement habits were measured over seven consecutive days using a 5‐item questionnaire and a single question about the number of bowel movements the participant had each day. The five questions were as follows: “(1) How much stool did you produce?; (2) Please select the appropriate rating which best describes the consistency of the bowel movement; (3) Please select the appropriate rating which best describes your straining during this bowel movement; (4) please select the appropriate rating which best describes your pain during the bowel movement; (5) Please select the appropriate rating which best describes your overall feeling of constipation.” The rating scale of 1–7 corresponded to very soft to very hard (questions 2), none to extreme (questions 3 and 4), or not constipated to very constipated  and the Rstudio (version 1.4.1106) interface with the following packages: car, dplyr, edgeR, gglot2, ggpubr, igraph, MASS, phyloseq, phyloseqGraphTest, pscl, purr, readr, RioNorm2, tidyr, and vegan. Alpha diversity measures  were analyzed using Friedman rank sum test followed by Wilcoxon signed rank exact test. Bray–Curtis index was used to assess beta diversity and analyzed using permutational multivariate analysis of variance (PERMANOVA). Principal coordinate analysis (PCoA) and graph‐based network analysis were used to visualize beta diversity. The differential abundance of taxa was analyzed using either a zero‐inflated Poisson model (for non‐over‐dispersed OTUs) or a zero‐inflated negative binomial model (for over‐dispersed OUTs). Data were filtered to remove taxa with <100 counts per million in over 90% of samples and were normalized based on relatively invariant OTUs prior to analysis  and p ≤ .05 was considered significant.The gut permeability proteins and bowel movement data were analyzed using SPSS 27.0 (IBM). A two‐factor repeated measures ANOVA test was conducted to examine the effects of fresh mango or low‐fat cookie consumption on gut permeability proteins  and bowel movement habits over time. Paired 33.1p = .049) and week 12 (p = .017) and higher ACE index at week 12 (p = .017) as compared to the mango intervention  and Simpson (p = .001) indices at week 4.The low‐fat cookie intervention showed higher Chao1 index at week 4 (3.2p = .005), but not between different time points or the interaction of the two. The significant difference in beta diversity between the mango and low‐fat cookie interventions was observed only at week 12 (p = .024). PCoA was performed to visualize the distance matrix. The first two principal coordinates (axis 1 and axis 2) of the PCoA explained 23.3% and 10.8% of variations of the data, respectively , a 1.3 log fold increase in Corynebacterium pyruviciproducens (p = .042), a 2.5 log fold increase in Mogibacterium timidum (p = .042), a 0.3 log‐fold decrease in Prevotella copri (p = .042), a 1.3 log fold increase Prevotella maculosa (p = .001), a 0.6 log fold increase in Salinicoccus luteus (p = .014), and a 2.7 log fold increase in Treponema refringens (p = .003) between baseline and week 12. Between baseline and week 12, the top species‐level taxa changes in the low‐fat cookie intervention led to a 1.2 log fold decrease in Alloscardovia omnicolens (p = .017), a 3.0 log fold increase in Cyanobacterium aponinum (p = .002), and a 3.3 log fold increase in Desulfovibrio butyratiphilus (p = .017).Species‐level analysis of the top taxa changes is shown in Figure 3.4No significant differences in ZO‐1 and CLDN2 were observed between baseline and week 12 within or between the mango and low‐fat cookie interventions (Table 3.5p < .05) in the mango intervention. There were no significant differences in the amount of stool produced from baseline to week 12 in the low‐fat cookie intervention. There were no significant differences found within either the mango or low‐fat cookie trials in bowel movement regarding consistency (soft or hard), strain, pain, or constipation. Similarly, there were no significant differences found in the comparison between mango and low‐fat cookie interventions.There were no significant differences in the frequencies of bowel movements in the mango or low‐fat cookie interventions Table . There w4This study examined the effects of daily mango consumption for 12 weeks on the gut microbiome, gut permeability proteins, and bowel movement habits compared to control, low‐fat cookie consumption.4.1The mango intervention decreased the richness‐based alpha diversity measures (Chao1 and ACE indices) while increasing the species evenness (Shannon–Wiener and Simpson indices) in comparison with the low‐fat cookie intervention. This may indicate that although the mango intervention resulted in fewer members of species as compared to the low‐fat cookie intervention, it led to a more even distribution of abundance across the species. Since species richness and evenness are both important determinants of microbial diversity, the Shannon–Wiener and Simpson indices provide more inference about the community composition  has been used as a health indicator, with a greater relative abundance of Firmicutes in comparison with Bacteroidetes being associated with higher risks of obesity and cardiovascular disease , and compare the effects of whole mango with other fruits.This study found that daily consumption of 100 g fresh mango increased the diversity of the gut microbiome after 4 weeks, with the greatest dissimilarities between diet interventions at week 12. Mango consumption results in an increased abundance of The authors declare that they do not have any conflict of interest.This study was approved by the Institutional Review Board of San Diego State University. Written informed consent was obtained from all study participants.


Ischnura elegans sampled from 31 rural and urban localities in three geographic regions: southern and northern Poland, and southern Sweden. Genome‐wide variation was assessed using more than 370,000 single nucleotide polymorphisms (SNPs) genotyped by ddRADseq. Associations between SNPs and the level of urbanization were tested using two genetic environment association methods: Latent Factors Mixed Models and BayPass. While we found numerous candidate SNPs and a highly significant overlap between candidates identified by the two methods within the geographic regions, there was a distinctive lack of repeatability between the geographic regions both at the level of individual SNPs and of genomic regions. However, we found “synapse organization” at the top of the functional categories enriched among the genes located in the proximity of the candidate urbanization SNPs. Interestingly, the overall significance of “synapse organization” was built up by the accretion of different genes associated with candidate SNPs in different geographic regions. This finding is consistent with the highly polygenic nature of adaptation, where the response may be achieved through a subtle adjustment of allele frequencies in different genes that contribute to adaptive phenotypes. Taken together, our results point to a polygenic adaptive response in the nervous system, specifically implicating genes involved in synapse organization, which mirrors the findings from several genomic and behavioral studies of adaptation to urbanization in other taxa.The complex and rapid environmental changes brought about by urbanization pose significant challenges to organisms. The multifaceted effects of urbanization often make it difficult to define and pinpoint the very nature of adaptive urban phenotypes. In such situations, scanning genomes for regions differentiated between urban and non‐urban populations may be an attractive approach. Here, we investigated the genomic signatures of adaptation to urbanization in the damselfly  This species has a complex life cycle with a long aquatic larval stage dedicated to development and growth and a short terrestrial adult stage dedicated to reproduction and dispersal  organisms , discovered and genotyped using ddRADseq, and the level of urbanization. These associations were tested using two genetic environment association analysis (GEA) methods, which use different methodological approaches to detect the associations and to correct for the effect of geographic structure. We included multiple urban and rural populations in three geographic regions, southern and northern Poland, and southern Sweden. This allowed us to test whether parallel signals of urban–rural differentiation are detectable at the level of individual SNPs or genomic regions, or whether the patterns of genomic differentiation between the rural and urban populations are largely region‐specific as phenotypes suggest , ranging between one‐two per year in southern Poland and one per year‐one per 2 years in southern Sweden , in three regions . We calculated the average value of imperviousness in a 1 km buffer around each locality (population) using Quantum‐GIS . The 1 km buffer zone was selected to approximately reflect the maximum dispersal capacity of the species. Although I. elegans generally moves within 200 m, dispersal events of >0.3–1 km were also noted , we used the percentage of impervious surface from the high‐resolution layer database of the European Environment Agency (2) using the R package geodata . WorldCover data are developed and validated in near‐real time from Sentinel‐1 and Sentinel‐2 data and have an overall accuracy of 75%. The data were projected using the Mollweide equal‐area projection. The fraction of each of the four land cover categories was determined for each location using buffer areas of a 1 km radius. The correlations of climate and land cover variables with the urbanization score were calculated using function correlation from R package correlation  by Novogene on NovaSeq 6000. Replicate libraries were prepared and sequenced for 29 samples to estimate the genotyping error.DNA was extracted using the Wizard Genomic DNA Purification Kit (Promega). Double digest RADseq libraries were prepared according to the Adapterama III High‐Throughput 3RAD protocol  and calling genotypes . The results of gstacks were filtered in populations. We retained RADloci present in at least five populations (‐p 5), in at least 20% individuals overall (‐R 0.2), and applying these filters haplotype‐wise (‐H); only biallelic SNPs with global minor allele frequency (MAF) of at least 2% (‐min‐maf 0.02) and observed heterozygosity not exceeding 65% (‐max‐obs‐het 0.65) were retained. For each SNP in each population, p‐value of the two‐sided test of Hardy–Weinberg proportions and FIS were also calculated.Reads were demultiplexed and cleaned with p‐value was identified. Then, based on these data loci were blacklisted if they showed: (1) heterozygote excess (p < 0.01) in more than one population, (2) heterozygote deficit (p < 0.01) in more than half of polymorphic populations with genotyped sample size of 8. Populations were run again with the compiled blacklist and the resulting vcf file was further filtered with bcftools 1.9  or 4 (X chromosome) were set to missing. Such a prepared dataset was used for subsequent analyses.The blacklist of RADloci to be excluded from further analyses because of an excess of heterozygosity  or an extreme excess of homozygosity was compiled as follows. First, for each autosomal locus in each population, the SNP with the lowest HWE 2.5To check whether genetic structuring in any genomic region departed drastically from the genome‐wide patterns, we used R package pcadapt  was performed in plink 1.9  in lfmm2. The p‐values were calculated with lfmm2.test from LEA, the p‐values for SNPs from putative collinear and inversion regions were combined and FDR corrected using p.adjust R function with method “fdr.” In BayPass 2.31, we tested for associations between individual SNPs and urbanization using the auxiliary variable covariate (AUX) model, providing the population covariance matrix Ω calculated under the core model  was calculated as the median from five independent BayPass runs, and the value of >20 was considered “decisive” evidence for an association . First, to test whether the candidate SNPs were closer to protein coding genes than other SNPs, we calculated the distance from each SNP to the nearest putative protein coding sequence (identifying the associated gene) using bedtools closest. The distances for the candidate and remaining SNPs were compared with the Mann–Whitney U test. Second, we wanted to test whether any Gene Ontology (GO) biological process category was over‐represented among genes associated with the candidate SNPs. In this analysis, we considered only SNPs located within 10 kb of protein‐coding sequences. The GO terms were assigned to I. elegans genes using eggNOG‐mapper v. 2 .More SNPs associated with urbanization were identified by BayPass Figure . At the 2 = 986, df = 1 p < 2e–16). Substantial overlap between LFMM and BayPass results was detected also at the regional level: in PL S all seven SNPs identified as significant in LFMM were also significantly associated with urbanization in BayPass analysis, while in SE this proportion was 29 out of 43 (both p < 2e–16). The 38 SNPs significantly associated with urbanization in any dataset by both LFMM and BayPass can be considered the “core” urbanization SNPs (coreUR). Many of coreUR show considerable differentiation of allele frequencies between the rural and urban populations, though the differentiation was not always consistent between the geographic regions  was mean annual temperature. Both LFMM and BayPass analyses were run to identify SNPs associated with this variable (temperature candidates). No temperature candidates were identified by LFMM for all regions combined, PL_S, or PL_N. In all other analyses, there was a highly significant overlap between urbanization and temperature candidates  38 coreUR defined in the previous section, and (ii) 1625 broadUR which encompassed all the SNPs significantly associated with urbanization in LFMM or BayPass analyzes at the level of the entire dataset or in any geographic region. The broadUR category probably contains many false positives. It should, however, be enriched in SNPs associated with urbanization and, if adaptation to urbanization is polygenic and region‐specific, then many relevant SNPs will only show a weak signal likely to pass the stringent U test, p = 0.87) or broadUR  and the remaining SNPs. Out of 228,834 SNP included in LFMM and BayPass analyses 64,723 (28.3%) were located within 10 kb of associated genes; there were 6121 such genes of which 3955 had GO terms assigned. Only five GO‐assigned genes were associated with coreUR and they were not enriched for any GO terms. Among 372 GO‐assigned genes associated with broadUR candidate SNPs, eight categories were enriched at the p‐value < 0.001, 56 at p < 0.01, and 153 at p < 0.05 (Table p = 1.7 × 10−5). Some other categories, mostly containing few annotated genes, such as those related to T cells or tooth development, were difficult to interpret in an insect. In the light of little overlap between regions in candidate SNP, we wanted to see whether the overrepresentation of “synapse organization” category was driven by a single geographic region. The category was significantly enriched among the candidate‐associated genes in PL S (p = 0.001) and SE (p = 0.023) but not in PL N though, interestingly, the ratio of the observed to the expected number of genes in the category was similar in PL N as in SE (13–6.6 vs. 13–6.3). Notably, there was little overlap of the “synapse organization” candidate‐associated genes between the regions—only a single gene was shared among all three regions, also each pair of regions shared a single gene, and there were 10, 10, and 14 genes unique to PL N, PL S, and SE, respectively. This indicates that the top enrichment result for the broadUR was built up by the accretion of distinct signals coming from all three regions.There was no significant difference in the distance to the nearest protein‐coding sequence between coreUR  by comparing allele frequencies of approximately 370,000 SNPs between multiple rural and urban sites in each region. The sampling of multiple populations within each region was done as part of a larger project investigating the response to urbanization in the context of a latitudinal gradient (https://ecopondproject.eu). Although we found numerous candidate urbanization SNPs, a notable result of our study was a marked lack of repeatability between the geographic regions, both at the level of individual SNPs and at the level of genomic regions. However, our results point to a polygenic adaptive response in the nervous system, particularly genes involved in synapse organization, which echoes findings from several other genomic , northern Poland (PL N), and southern Sweden (SE), were clearly genetically differentiated. Unfortunately, there are, to the best of our knowledge, no species‐wide phylogeographic studies on I. elegans, and especially males, were lighter and had a lower growth rate than rural individuals and that these phenotypic changes partially depended on the sampling latitude and rearing temperature. Such phenotypic variation was associated with adjustment of damselfly life history to warmer urban conditions likely imposing weaker seasonal time constraints and hence reduced larval growth rate compared to rural damselflies  shared ancestry between populations (Frichot et al., While the parallel response may not be detectable at the level of individual SNPs but be visible at the level of genes (Lee & Coop, 4.2Overall, parallel adaptation to urbanization is common at the phenotypic level (Santangelo et al., If the candidate pathways cannot be confidently identified beforehand, as in the present case, identification of GO categories enriched among genes associated with candidate polymorphisms may be useful and is broadly applied also in the studies on the genomics of urbanization (e.g., Harpak et al., Coenagrion puella (Tüzün, Op de Beeck, Brans, et al., The top GO category enriched among genes associated with broadUR candidates was “synapse organization,” a key constituent of the nervous system underlying behavioral and cognitive traits, which are among the most likely targets of selection during adaptation to urbanization (Ducatez et al., Interestingly, the “synapse organization” was significant only in two geographic regions, and in none of them was the top enriched category. As a consequence, the status of “synapse organization” as the top enriched category in the entire broadUR dataset was built up by the accretion of different genes associated with candidate SNPs in different geographic regions. Such a pattern suggests that different genes involved in the biological process “synapse organization” responded in different regions, or that our study was underpowered and we missed many significant associations. While both explanations are likely, the accumulating evidence from experimental evolution studies, where populations independently derived from the same source and adapting to the same selection pressures respond by changing frequencies of different alleles, indicates that heterogeneity and redundancy of polygenic adaptation are indeed common (Barghi et al., 5I. elegans, detected multiple candidate SNPs that may be involved in adaptation to urbanization. The signal at the level of SNPs and genomic regions was, however, mostly specific to particular geographic regions. Nonetheless, a highly significant overlap in the sets of candidates identified by the genetic environment association analysis methods we applied suggests that our set of candidates is indeed enriched in true positives, which would point to mostly polygenic adaptation to urbanization in I. elegans. The observed enrichment of the Gene Ontology category “synapse organization” among genes associated with candidate SNPs is consistent with this view and mirrors signals detected in a few previous studies of adaptation to urbanization in other taxa. Taken together, our results suggest that insects, similarly as birds, may adapt to urbanization by adjusting the allele frequencies of many genes affecting behavior and cognition.Our study of a highly mobile flying insect, the damselfly The authors declare no cinflicts of interest.Figure S1.Figure S2.Figure S3.Click here for additional data file.Table S1.Table S2.Table S3.Table S4.Click here for additional data file.