Cows are one of the oldest livestock that are bred for both meat and milk. There are only two local cow breeds in Latvia—Latvian Brown and Latvian Blue—which, until now, have not been genetically characterized. This study examined the genetic background of both local breeds in Latvia and identified genetic factors associated with mastitis, a common inflammation of the mammary gland that affects animal welfare and the quality of milk. Whole genome sequencing was performed on blood and semen samples, and the results from the obtained data show that both breeds had similar levels of genetic diversity compared with other breeds. The Latvian Blue breed showed a higher genetic variance compared with the Latvian Brown breed. Specific mastitis-associated genome regions were identified for each breed. This study provides fundamental insights into the genetics of local Latvian cow breeds and provides the first insight into the hereditary factors of mastitis in dairy cows. It may also facilitate the development of genetic tests to aid breeders in their attempts to maintain and improve local and foreign Latvian cattle breeds.Bos taurus breeds—Latvian Brown (LBG) and Latvian Blue (LZG)—characterized by a good adaptation to the local climate, longevity, and high fat and protein contents in milk. Since these are desired traits in the dairy industry, this study investigated the genetic background of the LBG and LZG breeds and identified the genetic factors associated with mastitis. Blood and semen samples were acquired, and whole genome sequencing was then performed to acquire a genomic sequence with at least 35× or 10× coverage. The heterozygosity, nucleotide diversity, and LD analysis indicated that LBG and LZG cows have similar levels of genetic diversity compared to those of other breeds. An analysis of the population structure revealed that each breed clustered together, but the overall differentiation between the breeds was small. The highest genetic variance was observed in the LZG breed compared with the LBG breed. Our results show that SNP rs721295390 is associated with mastitis in the LBG breed, and SNPs rs383806754, chr29:43998719CG>C, and rs462030680 are associated with mastitis in the LZG breed. This study shows that local Latvian LBG and LZG breeds have a pronounced genetic differentiation, with each one suggesting its own mastitis-associated SNP profile.Latvia has two local  The ‘wealth’ of a country can be measured by its animal breeds that are bred to facilitate the survival of resident populations within specific environmental conditions. The Convention on Biological Diversity recommends the conservation of different local breeds, as well as the related agricultural systems, as an optimal strategy for preserving genetic variation for further use in livestock development, thus emphasizing the need to promote ex situ conservation and the sustainable use of local genetic resources ,2.Latvia is home to two indigenous dairy cow breeds, Latvian Brown old type or ‘Latvijas brūnā govs’ old type (LBG), which, according to 2023 data, consists of 180 cows and 62 heifers, and Latvian Blue or ‘Latvijas zilā govs’ (LZG) with a population of 390 animals. Since 2000, the Ministry of Agriculture of Latvia has been actively involved in conservation efforts, implementing approved breeding programs for endangered varieties, like LBG and LZG cows. As of 2018, the conservation of local endangered varieties in accordance with the ‘endangered breed’ definition has been guided by Article 2 Point 24 of the Regulation (EU) 2016/1012. This regulation addresses zootechnical and genealogical conditions for the breeding, trade, and entry of purebred breeding animals, hybrid breeding pigs, and germline products into the European Union. It also includes amendments to Regulation (EU) No. 652/2014 and Council Directives 89/608/EEC and 90/425/EEC, while repealing certain acts in the area of animal breeding .Domestic cows that were reared on the territory of Latvia until the second half of the 19th century had small bodies, but they were very modest and durable. These cows had a relatively lower milk yield, which, starting in 1862, resulted in the import of the Angler variety to improve the local breeds . The othThe erosion of genetic resources experienced by both local cattle breeds often leads to the loss of beneficial traits, such as a naturally developed resistance to common diseases ,12. MastThe application of traditional selection approaches, which are based on phenotype and pedigree data, help to reduce the incidence of mastitis. Recently, it has become possible to complement traditional approaches  with breeding values estimated during genomic analyses. Since the cost of sequencing continues to decline, the number of studies based on whole genome sequencing is gradually increasing, and the accumulation of information on genetic variation that underlines disease resistance and other desirable traits can improve breeding programs and prevent the co-segregation of undesirable traits . Therefo® EDTA Tubes ) were acquired by a qualified veterinarian during routine general health checkups on the animals, which involved blood sampling. Kurzemes and Siguldas AIS kindly provided the employed bull semen samples.In Latvia, cows of local origin are mainly reared in small individual farms; the exception is the teaching and research farm Vecauce, with around 50 LBG old-type cows. In the summer season (from May to October), cows are grazed, while in the winter, the dairy cattle are housed in tied stalls and fed with silage and hay. The cows are milked twice a day using portable or semi-automatic milking machines. Similar hygiene management practices were maintained across all herds. The health management and control of the herds included in the study were conducted as part of routine veterinary surveillance. Impregnation of animals is primarily achieved through artificial insemination using semen from artificial insemination stations (AIS). Therefore, all employed blood samples from cows . The sample set included a total of 80 animals comprising 36 LZG cows, 36 LBG cows, and 8 bulls (four from each breed). Deep sequencing analysis was performed for 16 animals representing dominant paternal lineages in LBG and LZG breeds. Four unrelated bulls were selected from each breed, representing dominant paternal lineages with >60% ancestry from the respective breed. All bulls were born after 2010. The final decision to include a particular animal was based on the availability of bioproducts from the AIS resources.For the LBG breed, four unrelated cows  and four unrelated bulls  were from Odins, Rudme, Potrimps, and Ullors paternal lineages. These were previously used in the conservation of the breed. The 32 cows included in the shallow genome sequencing analysis were related according to the respective dominant lineages—the sample set included 6 daughters of bulls of the Rudme lineage, 6 of the Odins lineage, 7 of the Potrimps lineage, and 13 of the Ullors lineage . LBG aniThe LZG breed has, in general, a higher kinship connection; therefore, four LZG bulls  and four cows  were selected from different herds for deep genome sequencing. These animals represented only two paternal lineages, Gaujars Lietuvietis and LBG Potrimps. Thirty-two cows of the LZG breed from four farms were selected for shallow genome sequencing and were related according to their dominant lineages; samples were taken from ten cows of the Potrimps bull lineage, seven cows of the Gaujars bull lineage, three daughters of the Dzilnis lineage, and seven cows of the Darbonis lineage, and four samples were taken from two bulls with Lithuanian Light Grey ancestry related to Darbonis, and one sample was taken from a TYG bull . A graphMilk samples were obtained from 28 LBG cows and 21 LZG cows kept in six and seven herds, respectively . These wSubclinical mastitis is defined as the presence of inflammation within the normal-appearing mammary gland, but the diagnosis of an intramammary infection is based on the identification of the infectious agent. To isolate bacteria, milk samples (100 µL) were spread aseptically on Columbia blood agar base with 5% defibrinated blood and MacConkey Agar . Incubation was carried out at 36 ± 1 °C for 24–48 h. Bacterial isolates were identified via culture growth (recommended by ), morphog and 4 °C. Genomic DNA was then extracted from the buffy coat using the phenol–chloroform method following a previously established routine DNA extraction protocol [Prior to extraction, acquired blood samples were centrifuged for 15 min at 3488× protocol .g at room temperature, and the supernatant was removed, leaving the pellet and approx. 1 mL of buffer. The pellet was then suspended by vortexing for 10 s, and the resulting suspension was transferred to a clean 2.0 mL microcentrifuge tube. An additional 0.5 mL of buffer was added to the same 50 mL tube, vortexed for 10 s to collect any semen that adhered to the walls of the tube, and the suspension was transferred to the same microcentrifuge tube. Samples were then centrifuged for 2 min at 14,100× g, and the supernatant was discarded. Next, pellets were resuspended in a 300 μL buffer containing 100 mM TrisHCl (pH 8.0), 10 mM EDTA (pH 8.0), 500 mM NaCl, 1% SDS, and 2% β-mercaptoethanol. To release the DNA from its protamine complex, 40 μL of Proteinase K  was added to the buffered sample, which was mixed and incubated for 2 h in VorTemp 56 incubator  with a rocking platform at 55 °C and 200 rpm. An additional 20 μL of Proteinase K was added, and samples were incubated for another 2 h on the same rocking platform at 55 °C and 200 rpm. Finally, the robotic system KingFisher Duo  combined with the NucleoMag Tissue reagent kit  was used to purify released DNA. The purification procedure was carried out according to the user manual section ‘Genomic DNA From Tissue’ starting from the third step. During the final purification step, DNA was eluted in 200 μL of Buffer MB6 .A custom genomic DNA extraction protocol was designed for semen samples. Semen samples were mixed with 10 mL of buffer (150 mM NaCl and 10 mM EDTA (pH 8.0)) in a 50 mL tube and vortexed for 10 s. Next, buffered samples were centrifuged for 10 min at 3488× The quality of extracted DNA was evaluated using 1.2% agarose gel electrophoresis, while the quantity was assessed using the Qubit High Sensitivity DNA assay kit and the Qubit 2.0 fluorometer .Prior to the genome sequencing analysis, concentrations of DNA samples were normalized to an initial library input of 500 ng and sheared using Covaris S220 Focused-ultrasonicator , employing the manufacturer’s provided parameters to reach an average fragment size of 400 bp. Libraries were further prepared using MGIEasy Universal DNA Library Prep Set V1.0  according to the manufacturer’s recommendations. The libraries’ quality control was assessed using the Qubit High Sensitivity dsDNA assay kit and the Qubit 2.0 instrument, as well as the Agilent High Sensitivity DNA kit and the Agilent 2100 Bioanalyzer .Samples were then diluted and pooled to achieve at least 440 million reads per sample for deep sequencing (estimated coverage of approx. 45×) and 100 million reads per sample for shallow sequencing (estimated coverage of approx. 10×). Pooled and circularized libraries were used as templates for DNA nanoball (DNB) preparation and subsequently loaded onto the PE150 flow cell. Sequencing was carried out using the DNBSEQ-G400 sequencer and a DNBSEQ-G400RS High-Throughput Sequencing Set  according to the manufacturer’s instructions.Bos taurus reference genome ARS-UCD1.2_Btau5.0.1Y [Quality control and quality trimming of the obtained paired-end reads were performed using Trimmomatic v0.39  with optau5.0.1Y  using thau5.0.1Y . Mappingau5.0.1Y  SortSam.au5.0.1Y . All samau5.0.1Y  and the au5.0.1Y , and eacau5.0.1Y . BcftoolROH, and FROH>50kb values were assessed using the Shapiro–Wilk normality test and further used to compare their significance between LBG and LZB breeds using the Wilcoxon rank sum test at a p-value threshold of 0.05. Genetic differentiation (FST) was estimated using VCFtools with parameters of a 40 kb sliding window and a 20 kb step size. Individual heterozygosity was calculated using VCFtools. The proportion of heterozygosity was calculated as the ratio of the number of heterozygous sites divided by the total number of sites. To compare LBG and LZG breeds to other breeds that were obtained from the NCBI SRA, the set of LBG and LZG samples was randomly reduced to three samples per breed using bcftools. An additional check was performed on randomly selected samples to ensure that they were not located close to each other in the genetic distance tree and were not related (n = 3 per breed). Pairwise comparisons of (i) nucleotide divergence and (ii) heterozygosity among all breeds were conducted using the T-test with the Bonferroni p-value adjustment method with a p-value threshold of 0.05 employing package rstatix v.0.7.2.999. Visualization of the results was performed using package ggpubr v.0.5.0.999. For the runs of homozygosity (ROH) analysis, only variants with a minor allele frequency above 0.05 were retained, and ROH was then calculated using PLINK with the following parameters: minimum SNP count of 100, minimum ROH length of 10 kb, and only one heterozygous call within the ROH. The average ROH in kilobases per individual per chromosome was calculated, and the results of the ROH analysis were visualized using pheatmap v.1.0.12. The package PopLDdecay v.3.42 [ROH), calculated by dividing the sum of lengths of all ROH (FROH) or the sum of lengths of ROH longer than 50 kb (FROH>50kb) with the total length of autosomes  using the following [The SNP density plot per chromosome of LBG and LZG breed was visualized using the package rMVP  v.1.0.6. related . Sample y v.3.42  was usedollowing :FROH = LPrincipal component analysis (PCA) and structure analysis were conducted to investigate the genetic background. SNPs with high linkage disequilibrium were removed using PLINK. The pruned SNP data were used to estimate individual ancestry using the maximum likelihood method implemented in ADMIXTURE v.1.3 . The defp-values. The genome-wide association results were visualized using Manhattan and quantile–quantile (Q-Q) plots with the qqman [p-value was less than 1.0 × 10−9 and if their Bonferroni-corrected p-value was less than 0.05. All the above-described computations were performed using Riga Technical University’s High Performance Computing Center infrastructure.An association analysis was performed to determine whether the genetic background of the cattle was associated with mastitis resistance. First, variants were filtered using PLINK to retain only those with a minor allele frequency above 0.05. Pedigree information and disease status were collected for each animal and submitted to PLINK for association analysis. Genomic inflation estimator lambda (λ) based on the median value of the Chi-squared test was acquired through PLINK multiple-testing-corrected he qqman  package.2 units:Descriptive statistics, Pearson correlation, and linear regression analysis methods were performed in the Stata v.17.0  software. All SCC data were converted into SCC linear score (LS) according to the following formula (Equation (3)) and expressed in logOur strategy for assessing genetic diversity in two local cattle breeds and identifying genomic regions that determine breed-specific traits was based on a combination of deep  and shallow (32 cows) sequencing for animals of each breed. For LZG breed deep sequencing, we acquired a total of 3.5 billion sequencing reads with an average of 430,650,120  and 150 bp reads per sample, roughly corresponding to a 45.02× coverage . For the LBG breed, a total of 3.6 billion reads were obtained, with an average of 450,985,871  and 150 bp reads per sample, corresponding to a 47.14× coverage . The shallow sequencing of the LZG samples yielded a total of 3.6 billion sequences with an average of 112,412,214 reads per sample  and with an estimated average genome coverage of 11.75×  A. The shVariant calling on assembled sequencing data revealed that after quality filtering, there were 15,496,197 SNPs and 2,449,533 indels within the LBG data set, but out of these, 713,680 were multiallelic sites, and 50,123 were multiallelic SNP sites. Within the LZG data set, 16,248,091 SNPs and 2,519,762 indels passed the quality filtering criteria B, while A density map of the single nucleotide variation in each chromosome is shown in Comparing local and other widespread European breeds revealed considerable differences. The PCA analysis showed a pronounced genetic distinction between the LZG and LBG breeds A, as welA linkage disequilibrium (LD) analysis showed that the LZG breed had a slightly slower LD decay rate than the LBG breed C, but th−7 to 0.0323  in the LBG samples  in the LZG samples (p = 0.01249). Next, the LBG and LZG sample sets were randomly rarefied to three samples per breed to compare the nucleotide diversity between the other European breeds. The nucleotide diversity of LBG differed significantly from that of LMS (p = 0), LZG (p = 1.39 × 10−10), and HLS (p = 1.20 × 10−135), whereas LZG significantly differed from that of TYG (p = 1.51 × 10−7), BBL (p = 1.08 × 10−18), GER (p = 8.12 × 10−7), HLS (p = 3.56 × 10−69), HRF (p = 8.74 × 10−7), and LMS (p = 0) , followed by the BBL breed . The lowest average nucleotide diversity was observed for the LMS breed , followed by the HLS breed . The level of heterozygosity (p = 0.057); the level of heterozygosity was 0.2437 ± 0.031 for the LBG breed and 0.2384 ± 0.019 for the LZG breed. When the randomly rarefied sample depths of the LBG and LZG breeds were compared to those of the European breeds, we uncovered that HLS and LMS (p = 0.016) and LMS and TYG (p = 0.049) differed significantly in terms of heterozygosity (The estimated genome-wide nucleotide divergence (π) within a 50 kb sliding window ranged from 5.0 × 10 samples  and from samples . The hig (p = 0) . Overallzygosity F,G was azygosity . The higp = 2.2 × 1016). The average Tajima’s D statistic across all chromosomes was 0.769 ± 1.14 for the LBG breed   , whereas = 0.78) , indicatIn total, 422,266 ROH were obtained from the LBG breed data set, from which 10 were long (≥1000 kb), and 185 were of medium length (1000–500 kb). From the LZG breed, 416,381 ROH were identified; 3 of these were long (≥1000 kb), while 97 were of medium length (1000–500 kb). The majority of identified ROH in both breeds were relatively short. The number of ROH between 50 kb and 500 kb in length was 128,594 and 121,818 for the LBG and LZG breeds, respectively D. The avST statistics were calculated between individuals of the LZG and LBG breeds by each chromosome (ST statistics were observed for chr6:66.36~66.40 Mbp (FST = 0.72), chr11:18.60~18.64 Mbp (FST = 0.64), and chr6:61.94~61.98 Mbp (FST = 0.64). In contrast, the lowest weighted FST statistics were observed for chr1:158.02~158.06 Mbp (FST = −0.03) and multiple regions within the Y chromosome—9.58~9.62 Mbp; 11.06~11.12 Mbp; 11.96~12.02 Mbp; and 15.22~15.80 Mbp . Overall, the median of the weighted FST statistics across all autosomes was 0.047, whereas across both sex chromosomes, it was 0.037.To find the degree of differentiation between both local cattle breeds of Latvia, the Fromosome . The higBos taurus breeds. Starting from K = 4, the LZG and LBG breeds were separated from traditional European breeds, indicating a further genetic differentiation process. According to the calculated cross-validation value, the best fit was K = 1 (CV error = 0.45504), meaning that all breeds included in the admixture analysis have one ancestral component that is different from others. This finding is in concordance with the PCA results , a genetic distance tree was constructed see . OverallROH based on the sum of all ROH taken together was slightly but significantly higher in the LBG breed (0.197) than in the LZG breed .The inbreeding rate among the animals was assessed using genome-wide data on ROH. The FROH>50kb reached 0.12 for the LBG breed and 0.10 for the LZG breed (p = 0.02). However, the respective standard deviations of 0.039 and 0.033 for FROH and FROH>50kb in the LBG breed and 0.029 and 0.027 in the case of the LZG breed indicated a relatively high variation in interrelatedness among individual animals from both breeds.The inbreeding measures that were calculated considering only ROH that were longer than 50 kb or Fp > 0.05) between the LBG and LZG cow breeds in the first lactation, at the time of pathogen testing, and in the highest SCC scores in later lactations (p < 0.05) than in the first lactation in the LBG cows but not in the LZG cows. An overall comparison of the average SCC between farms was nonsignificant (p > 0.05). There was a moderate correlation between the SCC during the first lactation and the SCC during bacteriological testing .The level of SCC did not differ significantly  were found only in the LBG milk samples, while three  were specific to the LZG samples. Variations in the prevalence of bacteria in milk samples could be due to environmental factors and differences in resistance toward pathogens between the two breeds. The prevalence of bacterial agents in the cow milk samples is shown in Bacterial growth was confirmed in milk samples of 16 LBG animals, but no bacterial growth was detected in the other 16. The milk of only 11 LZG animals was confirmed to contain bacteria; there were none in the samples from 10 animals. The increase in SCC coincided with the number of major pathogens detected in the milk. From the tested set of bacterial species, six (S. haemolyticus (17.19%), followed by other Gram-positive bacteria Staphylococcus epidermidis and S. aureus (6.3% each), as well as E. faecalis and S. uberis (4.7% each). Therefore, during the subsequent genome-wide association analysis, we considered the consanguinity of the animals and the results that were gained during the microbiological analysis of the milk. Thus, the genomic data from 16 healthy and 16 mastitic LBG breed animals, as well as 10 healthy and 11 mastitic LZG breed animals were used to investigate genetic traits linked to mastitis resistance . Thus, the identified mastitis-associated SNP rs721295390T > A was located in the intergenic region on chromosome 10 . Only 2.6 kb upstream of this SNP was the location of the reverse-orientated LOC529823 gene that encodes C2 calcium-dependent domain-containing protein 4A, while further on in the distance of 19.8 kb was the forward-orientated gene VPS13C that encodes vacuolar protein sorting 13 homolog C. The frequency of this SNP in mastitis-affected cows was 0.09, whereas in healthy cows, it was 0.844. Furthermore, 14 diseased, 2 healthy, and 4 undiagnosed cows were homozygous for the reference allele (T/T), whereas 13 healthy cows and 1 diseased cow were homozygous for the alternative allele (A/A). Only one diseased, one healthy, and four undiagnosed cows were heterozygous (T/A) at the particular SNP location.In the case of the LBG breed, the quantile–quantile (Q-Q) plot D indicatCADPS) on chromosome 22 and cathepsin W (CTSW) on chromosome 29, respectively, and were accommodated between genes involved in the regulation of the immune system. Thus, the latter chr29:43998719CG>C (p = 0.003) was located 784 bases downstream of the treverse-oriented gene FIBP that encodes FGF1 intracellular binding protein and 6.6 kb upstream of the reverse-oriented gene EGF that encodes fibulin extracellular matrix protein 2 (EFEMP2). Both encoded proteins play a role in the regulation of inflammatory processes. The same SNP chr29:43998719CG>C was also located 6.9 kb downstream of the forward-oriented gene CCDC85B, which encodes a coiled-coil domain-containing protein 85B. It functions as a transcriptional repressor involved in maintaining the cytoskeleton integrity of epithelial cells. The frequency of this SNP chr29:43998719CG>C in mastitis-affected cows was 1, whereas in healthy cows, it was 0. More specifically, 11 diseased and 6 undiagnosed cows were homozygous to the reference allele (CG/CG), whereas 9 healthy and 10 undiagnosed cows were homozygous to the alternate allele (C/C). Only one healthy and three undiagnosed cows were heterozygous (CG/C). The other SNP in close proximity to the immune-system-related genes was rs462030680 (p = 0.009), located 134 bases upstream of the reverse-oriented gene FBRSL1 that encodes fibrosin-like 1 protein, which is suggested to be essential for stem cell maintenance and differentiation in mammals. The frequency of this SNP in mastitis-affected cows was 0.05, and in healthy cows, it was 1. In total, 10 diseased and 11 undiagnosed cows were homozygous for the reference allele (C/C), 10 healthy and 8 undiagnosed cows were homozygous for the alternative allele (G/G), and only 1 mastitis-diseased cow was heterozygous for (C/G). The last of the identified SNPs, rs383806754 (p = 0.001), which was mentioned previously, located within the intron of the CADPS gene, which encodes calcium-dependent secretion activator, was found exclusively in mastitis-diseased cows , and it was absent in the healthy controls . More specifically, 11 of the diseased cows and 8 of the undiagnosed cows were homozygous for the reference allele (TG/TG), while 10 healthy and 10 undiagnosed cows were homozygous for the alternate allele (T/T), and only 1 undiagnosed cow was heterozygous (TG/T).For the LZG breed, in the Q-Q plot G, a deviThe increased popularity of highly productive commercial cattle breeds has led to a dramatic decline in local dairy cattle breeds and the loss of valuable genetic resources. Two local Latvian breeds have small population sizes and are critically endangered. Knowledge of the genetic structure of the breed can provide essential support to improve breeding programs and to preserve the genetic integrity of local cattle breeds, which inspired us to perform whole genome sequencing analysis.The characterization of relatedness between the LBG and LZG breeds showed that both had retained at least some breed-specific genetic hallmarks. Although the differences were minor, and the admixture analysis indicated shared origins with other European breeds, the clustering patterns suggested distinct ancestry. Historically, LBG cattle have been crossbred with Traditional Danish Red and German Red Angler cattle, whereas LZG cattle had a stronger influence from Holstein cattle and several other breeds. Thus, an admixture of other European cattle might have disrupted breed-specific patterns. Apart from that, using different breeds to improve the LBG and LZG cattle may have contributed to distinct clustering patterns of both breeds observed in both the PCA and admixture analysis. This difference in admixture source can also explain the slightly larger distance between the LBG cluster and other breeds included in PCA. According to the genome-wide data, the Modern Danish Red, German Red Angler, and Modern Angler cattle appeared to have common ancestry, distinct from the closely related Holstein and Holstein Red breeds . PreviouST values , there was relatively low genetic differentiation between the two local breeds, and the short genetic distances among the LZG and LBG animals shown via dendrogram indicated a close interaction. For instance, the endangered breed German Black Pied cattle had an FST value of 0.069 compared to Holstein, supporting a shared history, whereas a three-times-higher value of FST 0.175 was estimated for Yakutian cattle, an old, genetically distinct native breed from Siberia with no influence from modern European cattle [Regarding the Fn cattle . Correlan cattle . None ofn cattle .The total average nucleotide diversity estimated for LBG and LZG indicated that Latvian breeds harbor relatively high levels of genomic variation compared with Holstein cattle. In our case, subsampling data from publicly available resources may have biased the estimates for other breeds, which appears to be the case for Limousin cattle . HoweverHeterozygosity is another measure that is often used to track the amount of genetic variation retained by the population. It was higher among the LBG animals than the LZG animals, which is opposite to the estimated nucleotide diversity that was slightly lower for the LBG breed. This result was probably due to the high proportion of offspring of a single LZG bull. Similarly, the discrepancy between the two estimates among German Black Pied cattle, a high rate of nucleotide diversity, and low heterozygosity was explained by the limited number of breeding bulls . In geneGenome-wide LD-based measures serve as good indicators of the processes shaping a breed’s genetic background . A moderROH of 0.088, estimated by summing all the ROH lengths per individual, was observed for the Evolene breed. The total contemporary population of these animals is around 200 cows. Despite a similar population size, the inbreeding rate of Evolene cattle was notably lower than FROH 0.197 and 0.179 observed in the LBG and LZG breeds, respectively [ROH>50kb values of 0.12 and 0.10, Neumann and colleagues reported a slightly higher inbreeding coefficient of 0.16 for German Black Pied cattle native to the North Sea region, derived from the sum of ROH longer than 50 kb. The breed is endangered, and its population consists of approximately 2500 animals. Although the FROH>50kb values of other breeds that were included in the study varied from 0.14 for Modern Danish Red to 0.29 for Jersey, which typically indicates increased inbreeding, for the Hereford, Angus, and Holstein breeds, the FROH>50kb values were 0.26, 0.23, and 0.20, respectively [A relatively slow LD decay, moderate levels of heterozygosity, and measures based on the proportion of genome covered by ROH indicate comparatively high inbreeding for the two local breeds. Among Alpine cattle, the highest inbreeding rate Fectively . On the ectively .ROH value in the LBG breed [ROH>50kb value for these animals was 0.14 [Our data were more comparable with the inbreeding rates obtained by studies investigating the genetic diversity of Original Braunvieh cattle and four Danish dairy cattle breeds with different demographic histories ,58. AmonAccording to an analysis of blood group alleles in Baltic cattle breeds, LZG showed the lowest diversity of alleles. The homozygosity levels for LBG cattle were missing, but the degrees of homozygosity in the Estonian Red and Lithuanian Red cattle breeds were 5.4% and 7.4% . PedigrePED) observed by others and the inbreeding rate estimated from genome-wide data were in agreement on both populations being inbred, inbreeding coefficients based on ROH were at least twice as high and contradictory to FPED data, were increased in LZG compared with LBG cattle [ROH estimates. The structure of the ROH in the genomes of the LZG cattle could be disrupted by a high rate of crossbreeding with several different breeds. Similarly, among sheep breeds, genomes of crossbreed animals comprised significantly less ROH than purebred ones [Although the blood group typing data and pedigree-derived measures of relatedness , which is involved in defense mechanisms against bacterial invasion in mastitis. The FGF1 was among the genes induced by the E. coli infection of primary mammary epithelial cells in the udder [FGF1 induces calcium mobilization and the activation of NF-κB and other signaling pathways within immune cells with the net result of reduced inflammation [EFEMP2 could play in the development of mastitis is less clear. The results of previous GWAS studies suggested that the EFEMP2 locus is affecting cattle meat quality [CCDC85B may promote the progress of inflammation of udder tissue through mechanisms related to those of C2CD4A. The activation of CCDC85B enhances β-catenin degradation, retaining NF-κB activity and thus inhibiting the Wnt/β-catenin cascade. The inhibition of the Wnt/β-catenin pathway prevents the re-organization of the cytoskeleton of epithelial cells. Preserving the cytoskeleton structure maintains the integrity of the endothelial barrier and impedes bacterial invasion within the tissue [CADPS. The locus harbors genetic variants correlating with body conformation traits, including bone quality, leg and feet traits, and eating behavior among cattle [CADPS within immune cells has been shown to modulate inflammatory responses of intestinal endothelium during chronic inflammation, which is characteristic of celiac disease [CADPS may be involved in the development of mastitis through multiple mechanisms [FEZF2 found upstream from the rs383806754 has been linked with mastitis in other studies [FEZF2 expression was increased in the mastitic quarters of affected cows [FEZF2 was suggested to be involved in immune tolerance and defects of the gene, causing autoimmune diseases in humans [CADPS may have a regulatory effect on the expression of FEZF2.Genetic variants located within the genomic region on chromosome 29 overlapping y cattle ,73. The  killing . The dirhe udder . The expammation ,76. The  quality . Anothere tissue ,78,79. Ag cattle . Other sg cattle . In huma disease . It can chanisms ,81,82. Y studies ,83,84. Ated cows ,84. The FBRSL1, which encodes a protein with RNA binding activity belonging to the polycomb complex [The fourth locus that correlates with mastitis among LZG animals comprises  complex . In huma complex . Its fun complex ,89. Udde complex .To sum up, the acquired SNP profiles were distinct for each breed, suggesting that the genetic composition of the LZG and LBG breeds influences the association signal. Although genetics appears to have a significant influence on the association analysis outcomes, it is important to consider the potential impact of environmental factors on mastitis development. Previous studies have highlighted the contribution of various factors, such as cattle housing conditions and milking routines, among others, to the manifestation of mastitis ,14,17,18The conducted association analysis supports the presence of association signals within previously detected candidate genomic regions on chromosomes ,73,83,84We completed a genome-wide characterization of two indigenous cattle breeds of Latvia. Even though the crossbreeding of LZG cattle is particularly common, the animals representing the LBG and LZG breeds still carry some distinctive genetic hallmarks that are characteristic of the original ancestral breeds. Until now, LBG and LZG cattle breeds have retained substantial genetic diversity. However, moderate levels of heterozygosity and elevated inbreeding indices indicate an urgent need to preserve both breeds’ genetic integrity. Some proportion of original genetic traits may have been already irreversibly lost, which hinders the restoration of the original genetic profile of both breeds. However, local breeds are still of genetic value and represent a part of cultural heritage. To preserve these resources, it would be necessary to continue the genetic characterization of the remaining cattle. The accumulation of genetic data would facilitate the selection of the most representative animals for breeding and help to choose breeds that are most suitable for crossbreeding, which might be necessary to retain healthy genetic diversity. Highlighting genetic variants that potentially increase disease susceptibility can improve pedigree-based breeding programs by reducing the possibility of the accumulation of multiple risk alleles that compromise the fitness of LBG and LZG breeds. Genomic data could also be used to establish ‘living gene banks’, improving the odds of preserving local cattle breeds. Apart from assisting in the management of national breeds, research on local breeds improves our knowledge of genetic resources that are globally available to fulfill the requirements of cattle breeding development.


Diplodia seriata causing black rot canker of apple was investigated in this study. All the isolates were included for investigating the in vitro mycelial growth, conidial dimensions, and pathogenic variability on two-year-old potted apple seedlings. The ISSR approach was used to investigate the molecular diversity of D. seriata. Mycelial growth rates were found to vary significantly amongst the isolates; however, there were no major variations seen between the different geographical groupings of isolates. Pathogenicity tests revealed variations in the size of cankers among the isolates indicating the presence of virulence variability. The isolates were segregated into three virulence groups based on canker length. The Bayesian analyses of ISSR data divided the isolates into two genetic clusters. The genetic clustering of the isolates revealed no relationship with geographical origin of the isolates. Furthermore, no direct relationship of genetic clustering was observed with morphological or pathogenic variability. The ISSR primers revealed very high level of variability in D. seriata; however, no distinct populations of the pathogen existed which is an indication of high level of gene flow between the diverse geographical populations. According to our knowledge, this is the first thorough investigation on the diversity of D. seriata associated with apple black rot canker in India.Apple cankers are extremely destructive diseases threatening the global apple industry through direct and indirect losses. The population structure of the pathogens is of paramount significance for the development of efficient management strategies. Therefore, phenotypic, pathogenic, and genetic diversity of  Malus domestica) is the oldest temperate fruit which is very popular around the world and assumes an excellent global market. It has varied size, shape, color, taste, texture, aroma, and nutritive value fulfilling the needs and desires of global population. Apple is cultivated in temperate and subtropical areas and ranks fourth globally in production after citrus, grapes, and banana1.Apple  indicates that the host range for D. seriata now is significantly wider, with over 200 species and 130 genera of herbaceous and woody plants functioning as hosts11. It has been reported to produce different symptoms like cankers, dieback of shoots, fruit rot, and leaf spots on a wide category of horticultural crops12. Diplodia seriata (syn. Botryosphaeria obtusa) is an important pathogen of apples inciting diseases like frog-eye leaf spot, black rot, dieback, and cankers13. The occurrence of black rot on apple fruit was first reported by Peek from New York in 1879, whereas its leaf spot phase was reported by Alwood in 1892 and its destructive canker phase (Black rot canker) was reported by Paddock in 189914. Mundkur and Kheswala15 reported the smoky blight  from imported apple plants in Mysore, India. Infection occurs through wounds or by direct penetration through natural openings18 followed by colonization of the healthy tissues.20. However, Singh21 recorded the development of cracks along the lesion margins; thus, temporarily restricting canker elongation. In advanced stages the bark becomes loose and gets separated from the wood. The initial symptoms are identified by brown discoloration of the bark on branches and twigs followed by leaf chlorosis. The bark cracks as the disease spreads further into the timber, revealing the reddish-brown discolored wood below. Internal browning of the woody tissues is seen on splitting the infected twigs along the axis. The spurs, twigs and branches above the cankered portion are killed without developing any canker symptoms. On the bark of diseased or dead branches and twigs, many black pycnidia of the fungus may be seen22.The smoky or black rot canker develops on branches, limbs and trunks as small, sunken, reddish-brown lesions which rapidly enlarge lengthwise, become elliptical, develop alternate rings, turn smoky and partially or completely girdle the affected part of the plant. While superficial roughening of the bark is typical, in certain instances the bark is destroyed up to the wood and totally shatteredD. seriata has been evaluated on shoots, fruits, and leaves of apple in some countries24. The experimental data on the pathogenic nature of Diplodia spp. on woody plants is controversial25. The studies on the pathogenicity of different D. seriata strains on various hosts and in different regions have shown inconsistent results26. In England and New Zealand, it is considered as secondary and weak pathogen of apples27, while reported as highly pathogenic on apples in the USA29. Similarly, contrary reports on the pathogenic nature of D. seriata on grapevines have been reported from different parts of the world12. Although different symptoms like dark vascular discoloration, extended necrotic lesions on shoots and formation of cankers have been linked to pathogenicity of Botryosphaeriaceae species30, pathogenicity and virulence of the canker causing fungi is normally estimated by measuring their capability to develop brown necrotic lesions beneath the bark and the lesion size, respectively12. Larignon31 studied the pathogenic variability in D. seriata and divided the isolates into four virulence groups based on variations in lesion size. The variations in pathogenicity level of D. seriata isolates on grapevines has been reported in earlier studies32. Savocchia33 also recorded pathogenic variability in D. seriata isolates based on intraspecific variations within this fungus.Pathogenicity of 53 have been proved effective35. The relative participation of telomorphic and anamorphic forms contributes to genetic diversity of a species. For Botryosphaeriaceae species, the telomorphs are rarely found in nature6 and the reproduction is mainly asexual under natural conditions36. However, exchange of genetic material can take place between compatible genotypes by parasexual recombination37. In Spain the genetic diversity of D. seriata isolates derived from grapevine was studied by Martín38 using AFLP markers but no data on pathogenic diversity was provided. Elena12 studied phenotypic, pathogenic, and genetic diversity of D. seriata on grapevine and reported high level of diversity within populations but no relationships among the genetic grouping and the virulence of different isolates was observed. Investigations on genetic variance between the populations of Lasiodiplodia theobromae revealed very low gene flow and genotypic diversity between the geographic populations, and increased gene flow and genotypic diversity among the pathogen populations resident on different host plants39. Genetic and virulence variability in the isolates of Neofusicoccum parvum was reported by Baskarathevan40. Nevertheless, no association was found between genetic clustering and isolate virulence. Genetic diversity existed between 66 isolates of Neofusicoccum luteum belonging to different pathogenic groups; however, the pathotype–genotype relationships were not found41. The genetic diversity studies on Togninia minima reported no significant differences in virulence between the genetic groups42. To the best of our knowledge, no comprehensive studies on the combined genetic, phenotypic, and pathogenic characterization on the isolates of D. seriata associated with black rot canker of apple have been undertaken.For genetic diversity analysis, inter-simple sequence repeat (ISSR) or random amplified microsatellite (RAMS) techniqueD. seriata responsible for black rot canker of apple trees in India. The pathogenicity assays conducted on young potted apple seedlings were used to estimate the pathogenic variability, whereas mycelial growth rates and conidial dimensions were used for phenotypic characterization. The final aim of our investigations was to verify the potential existence of distinct populations of D. seriata in different geographical regions based on combined morphological, pathogenic, and genetic studies, and the expansion of our understanding regarding D. seriata which may help us in understanding the pathogenic nature of D. seriata in apple and will have an impact on the efficient disease management strategies.The main purpose of the present investigation was to acquire more satisfactory comprehension of the phenotypic, pathogenic, and genetic diversity of D. seriata was assessed by growing the isolates on PDA. All the isolates were involved in this investigation . The mean mycelial growth rate for all the isolates with 95% confidence interval was 2.66 ± 0.87 cm, with minimum and maximum mycelial growth rates as 2.13 cm and 3.18 cm, respectively. The variation in radial mycelial growth of the isolates had no relation with the grouping of isolates based on geographical origin as well as with virulence groups. The statistically significant differences in growth rates were not observed among the geographical groups of isolates , 0.23 µm between group 1 and group 3 , 0.81 µm between group 1 and group 4 , 1.10 µm between group 2 and 3, 1.68 µm between group 2 and 4, 0.58 µm between group 3 and 4 in length. Similarly the absolute differences in means of width among the geographical groups were as; 0.14 µm for group 1 and 2 , 0.25 µm between group 1 and 3 , 0.50 µm between group 1 and 4 , 0.39 µm between group 2 and 3, 0.64 µm between group 2 and 4, 0.25 µm between group 3 and 4, respectively. The mean L:W ratio of the geographical groups was 2.18 ± 0.08 for group 1, 2.07 ± 0.12 for group 2, 2.26 ± 0.07 for group 3 and 2.36 ± 0.07 for group 4 respectively  were polymorphic  band patterns identical to band arrangements in ISSR characterization were detected in 21 and the proportion of coincident bands exceeding 90% were observed in 35 combinations. Among all the combinations the coincident bands were estimated to be present with an overall percentage of 94%.Four distinct clustering techniques were used to determine the most probable number of communities that the samples obtained would represent, assign individuals to these populations, and estimate the degrees of variance. Except for one isolate, i.e. DS38, which split as an independent lineage, the cluster analysis based on the unweighted Neighbor-joining approach yielded a dendrogram that grouped all the isolates representing four geographical populations into two primary clusters. The cluster first comprised of 26 isolates while as cluster second comprised of 21 isolates. The assignment of isolates into these two clusters was independent of their geographical background as both the clusters contained individuals from all the four geographical populations. Both the major clusters were further divided into smaller sub-clusters which were also independent of the geographical origin of the isolates. This demonstrates that genetic diversity exists both inside and among population isolates Fig. .Figure 4The average number of observed alleles (Na) and effective alleles (Ne) across all the loci varied between 1.385 and 1.662 and 1.345 and 1.393, respectively, across the four distinct regional populations . The highest number of observed alleles (1.662) were found in the population SH belonging to district Shopian of the valley, while as lowest number of observed alleles (1.345) were found in the population GN belonging to district Ganderbal, with mean value of 1.504. Again, the highest effective allele number (1.393) was found in the population SH while as the lowest number of effective alleles (1.345) were found in the population PL belonging to district Pulwama, with an average of 1.372. Similarly, the values of gene diversity (h) and unbiased gene diversity (uh) ranged from 0.218 to 0.242 and 0.238 to 0.264, respectively. The highest values of h (0.242) were recorded for the population SH pertaining to geographic locations of district Shopian and lowest values of h (0.218) were recorded for the population PL pertaining to geographic locations of district Pulwama, with an average of 0.228. Similarly, the highest values of uh (0.264) were recorded for the population SH belonging to geographic locations of district Shopian and lowest values (0.238) were recorded for the population PL, with an average of 0.248. Based on the Shannon’s information index (I), the highest diversity was recorded in the population SH (I = 0.377) and lowest diversity was recorded in the population PL and GN (I = 0.341), with an average of 0.350. The percentage of polymorphic loci among the populations ranged from 66.15% in GN to 81.54% in SH with an average of 72.31% . Although just 18% of the overall genetic diversity was found across populations from various geographical locations, most of the genetic variation (82%) was found within populations  Table .Table 8AP = 0.01). Pairwise PhiPT values estimated the degree of genetic divergence between the four populations. The average degree of genetic similarity was calculated to be 0.178   Table . The pope) Table . The paie) Table .Table 9Pstructure software divided the 48 D. seriata isolates into two genetically distinct clusters. The log likelihood values (Ln P(D)) increased from K = 1 to K = 2 and was maximum at K = 2 (ln P(D) = 2145·68). The standard deviation showed a slow increase from K = 1 to K = 2 and thereafter it showed a rapid increase from K = 3 to K = 10. This showed that the population structure of the D. seriata pathogen population is best explained by K = 2 clusters. This is further strengthened by the value of ∆K which was highest at K = 2 (∆K = 101·39) and after that it decreased at a very fast rate. The highest value of ∆K that determines the best fit of K was derived by employing STRUCTURE HARVESTER  was carried out with Genalex software on the whole data set to verify the consistency of genetic differentiation clustering performed by different clustering methods. The two-dimensional PCoA plot revealed that 15.45% and 9.20% of the total genetic variation is represented by the coordinate 1 and coordinate 2, respectively. It is evident from the PCoA plot that except two individuals as outliers and two small groups were formed, and all the other individuals formed a common group, however the individuals in all the groups were intermixed . Similar results were recorded by Elena et al.12 who reported 88% polymorphism in 83 D. seriata isolates from Spain. Employing AFLP markers Martin38 recorded 86% polymorphism in the isolates of D. seriata derived from Spain. With UP-PCR technique Billones-Baaijens et al.41 recorded 93% polymorphism in the isolates of N. luteum. Using the same technique, Baskarathevan et al.40 also recorded 93% polymorphism in 60 isolates of N. parvum. Many factors such as gene flow, recombination , mutation and adaptation of the pathogen to diverse host species may be responsible for the presence of high genetic diversity in D. seriata. Although Hesler recorded the formation of perfect state (Botryosphaira obtusa) for the smoky canker pathogen on apple twigs but other researchers from India and other countries failed to report any sexual state in field22. Thus, further investigations are required to be undertaken both under natural field conditions and at genetic levels to verify whether some hidden telomorphic state is responsible for the high genetic diversity in this fungal species. Estimates of pairwise FST were low in geographical populations. This indicates that there is frequent gene flow between populations probably due to movement of infected planting material.Clustering of D. seriata as highly pathogenic on apple and indicated variability in virulence, but the pathogenic variability was not correlated to either the genetic variability or the geographical origin of the isolates. To the best of our knowledge, this combined phenotypic, pathogenic, and genetic variability of D. seriata isolates causing black rot canker, dieback, and fruit rot of apple in India is studied for the first time and it will help in understanding the pathogenic nature of the D. seriata populations and development of more effective management strategies in future.The morphological differences shown by the isolates in phenotypic characterization did not show any correlation with the genetic clusters. Moreover, the pathogenicity tests revealed 2) were taken along the margins of canker lesions by using sterilized blade and the tissue bits were sterilized for 60 s in 1% sodium hypochlorite solution. The bits were washed thrice with sterilized distilled water to eliminate the remains of chemical followed by drying on blotting paper and inoculated on acidified PDA. The inoculated plates were placed under incubation at 25 ± 1 °C in the darkness. All the isolates of D. seriata collected from different geographical areas were purified by single spore technique60. D. seriata was identified based on morphological characters as per the descriptions of fungus given by Phillips13. In all, 48 isolates  @ 0.3% as a spray to eliminate the existence of any pathogens which may be present on the host surface. The pots were kept inside a polyhouse and timely irrigated to prevent the young apple seedlings from water stress and intermittently sprayed with distilled sterilized water to maintain high humidity inside the chambers. The inoculations were done on dormant apple twigs. Each isolate was inoculated on three twigs and the tests were performed as per the following procedure.Pathogenic variability was studied by performing pathogenicity tests of all the 48 isolates on healthy two-year-old potted apple seedlings (cv. Red Delicious grafted on Quince root stock) following the procedure adopted by SpiersD. seriata.On the selected twigs, after surface sterilizing the designated area with 70% ethanol, a 5 mm horizontal cut was given cutting the bark of the twig. Starting from the mid-point of the first cut, another vertical cut of 5 mm was made. The bark of this T-shaped cut was loosened with the help of a sterilized scalpel. A mycelial disc (4 mm) was put beneath the bark of incision and a cotton swab moistened with sterilized water was placed on the inoculated cut followed by wrapping with adhesive paper tape. The control was inoculated with plain media (PDA) disc and the incisions were covered as described earlier. The pathogenicity tests were regularly tracked for canker formation. Observations in terms of symptom development and lesion size by different isolates were recorded. The pathogen was re-isolated from the inoculated twigs to fulfill Koch's postulates. For re-isolations 1 cm pieces of wood after removing bark were cut at the two ends of canker lesions and sterilized in ethanol (70%) for 4 min, blotted dry and inoculated on Petri plates containing acidified PDA. The plates were kept under incubation at 25 ± 1 °C and observed for morphological characters of D. seriata from the four geographical locations were included in this study. Each Petri plate containing PDA was inoculated in the center with 5 mm culture bit of the actively growing isolate of D. seriata followed by incubation of the plates at 25 ± 1 °C. Each isolate was grown on four PDA plates. The observations on radial mycelial growth were recorded after 72 h by taking average of four radial measurements perpendicular to each other. The test was conducted thrice for the purpose of accuracy.All the 48 isolates of 64. For each isolate the conidial dimensions (length and width) of 50 conidia were recorded, and the length: width ratio was estimated.Conidial characteristics such as shape, size, color and septation of all the 48 isolates were assessed on oatmeal agar medium. The cultures were kept on a bench in the laboratory for 4 weeks at about 20–25 °C for inducing pycnidia formation under diffused sunlight. The spore measurements of each isolate were recorded under light microscope  at 100× magnification by preparing semi-permanent slides in lactophenol under 10 random microscopic fields after calibrating the microscope following standard proceduresD. seriata were grown on PDA broth in Erlenmeyer flasks. Mycelium was harvested by filtering the contents of the flask through a double layered filter paper, dried and stored at − 80 °C. Adopting modified CTAB (Cetyl trimethyl ammonium bromide) method62, total genomic DNA was extracted from all the isolates. The DNA was kept at 4° C for amplification and stored at − 20° C for future use.For raising enough mycelium for DNA extraction, all the isolates of D. seriata. PCR amplifications were performed in 0.2 ml PCR tubes in a T-Gradient Whatman Biometra thermal cycler with 50–60 ng of genomic DNA per isolate. The final volume of PCR mix was adjusted to 25 μl per reaction with RNAse-free water.A set of 17 ISSR primers namely (CAG)5, (ACA)5, BDB(ACA)5, (AG)5, (AT)8B, (CA)5, (GA)5YC, (TC)8RA, (CCA)5, (CGA)5, HBH(AG)7, (CT)5, (TG)5, (AG)5YC, (AG)5YA, (TG)8RC and BBD(AAC)5 were chosen for conducting preliminary screening against 10 randomly selected isolates to study the polymorphism. Five primers which were consistent in polymorphism during preliminary screening were selected for ISSR characterization of all the 48 isolates of The reaction mixture in PCR tubes were given short spin or vortexed in microfuge and placed in 96-well thermal cycler. PCR amplifications were conducted in thermal cycler programmed for initial step at 94 °C for five minutes followed by 35 denaturation cycles at 94 °C for one minute, annealing at appropriate temperature Table  for one D. seriata and run at 5 V/cm and visualized under UV light. The photograph of resultant banding pattern was taken using Alfa Imager gel documentation system. The size of ISSR alleles was determined by their relative positions with respect to DNA ladder (100 base pair). The amplification reactions of all the primers were repeated thrice for a single DNA extraction of each of the isolates. Further, for band scoring only clear and reproducible bands were taken into consideration.The quality of PCR products was evaluated on 2% agarose gel. TAE (0.5X) was used to prepare the gel and ethidium bromide at 0.5 μg/μl was added to it. The gel was loaded with amplified products of all the 48 isolates of 69. For each marker the alleles were calculated in all the isolates by numbering the alleles as 1, 2, 3 and so on, starting from the allele possessing maximum molecular weight. The bands were visually scored as 0 (absent) and 1 (present). The binary data generated by ISSR primers was analyzed by cluster analysis utilizing the program NTSYS-pc version 2.0263. Based on shared bands among the isolates, similarity was estimated from the data generated by all the 5 ISSR primers using Jaccard’s coefficient. The NTSYS software was utilized for determining the Nei and Li65 coefficients to ascertain the similarity between the isolates of D. seriata. The investigation of genetic diversity among the isolates of D. seriata was done by analysis of the band arrangements using a Bayesian clustering approach executed in STRUCTURE v.2.2.367 considering a population admixture model wherein within population correlations of allele frequencies are worked out. The runs for each K value (1 to 10) were set for 20 independent replications having a burn‐in period of 100,000 accompanied by 500,000 iterations of the Markov Chain Monte Carlo (MCMC). The posterior probability of the data (ln P(D)) was estimated utilizing the ad hoc ΔK statistic, based on rate of change between successive K values, and this estimate was later employed for inferring the uppermost level of structure in the dataset67. The highest values of Ln P(D), which represents the posterior probability of the data for a certain K, and ΔK were used to determine K 76. The sample populations were divided into genetic groupings using bar graphs that represent individual assignment probability. By using Structure Harvester v6.0 to generate the K values, the best-fit population cluster number (K) was verified76. Employing ARLEQUIN v. 3.568, AMOVA was used to find out the differences in assigning the isolates to different clusters which were obtained after Bayesian analyses.The banding pattern of each primer was scored as 1 (band present) and 0 (band absent) and the pattern was converted into a binary matrix with the help of MS Excel. The binary data matrix was used to work out TNB , NPB (number of polymorphic bands), and PPB (percentage of polymorphic bands). The Jaccard’s coefficient of similarity was calculated in the PAST (v 4.0) software by making pairwise comparisons between the individual isolates. Furthermore, a dendrogram was constructed with the help of same software by adopting the UPGMA method. The cophenetic correlation coefficient was worked out by the PAST program for measuring the goodness of fit between the cophenetic matrix and the distance matrix71. Microsatellite data set were analyzed for basic genetic diversity indices such as, N: Sample size; Ppl: percentage of polymorphic loci; Na: observed number of alleles; Ne: effective number of alleles; I: Shannon’s information index; h: diversity; uh: Unbiased diversity using population genetic software GenALex 6.50371.Further, the pairwise population differentiation (PhiPT) was also worked out by utilizing Genalex 6.503 packageThe principal coordinate analysis (PCoA) was conducted by employing Genalex software to generate a coordinate graph of the most significant axes to verify the clustering pattern. Distribution of the genetic variation into two components viz. within populations and among the populations was calculated by performing the analysis of molecular variance (AMOVA) in Genalex at 999 permutations.D. seriata were primarily grouped into populations based on geographical origin. The pathogenicity experiments were conducted following randomized complete block design under poly house conditions. Groups based on geographic origin and those generated by the STRUCTURE analysis were considered as independent variables. ANOVA (One‐way) and posterior Tukey's Honestly Significant Difference tests were performed on dependent variables to find out the differences between the mean values. The molecular data generated during the study was analyzed with NTSYS- 2.02e; Arlequin v. 3.5; GenAlex 6.503; PAST 4.0 and STRUCTURE v. 2.2.3 as described earlier. The remaining data was analyzed by SPSS (ver. 18) and SAS (ver. 9.2) software.To estimate the population genetic structure and examine the distribution of genetic diversity, the isolates of


Communicating the diagnosis of a genetic entity/rare disease to a patient or their parents is a complex process; it requires the doctor, pediatrician, or geneticist to display good communication skills and knowledge in a moment of uncertainty and disorientation for the family group, and sometimes in an inappropriate environment or under time constraints.A genetic diagnosis can be made for patients at different life stages: prenatal, at birth, and later, and even in adulthood, as is the case with some types of cancer or neurodegenerative entities. If diagnosis occurs before birth, it must be confirmed at the time of birth. This requires that staff be responsible in preparing to communicate the information, which should ideally be transmitted to both parents at the same time. Furthermore, if it is a presumptive clinical diagnosis, or if it has been confirmed through a genetic study, this must be explained in a way that is easy to understand.Today, it is common for family members to look for information on the internet, so it is necessary to emphasize that this information must be obtained from a reliable source, such as expert publications; moreover, it must be emphasized that the clinical case being described represents an individual, and may not be relevant to other individuals with the same genetic entity. Additionally, it must be highlighted that this process should preferably take place in person and not via phone call or message. The professional must address doubts in a precise manner based on up-to-date information and provide a description of the genetic entity; additionally, they may provide information about support groups or on local or national foundations.Throughout this process, it is necessary to create a relationship based on trust and empathy. The professional should pause if a family member begins to cry, which forms part of the acceptance process and subsequent learning, and they must demonstrate understanding of the individual’s feelings. It is necessary to avoid inappropriate terms that do not contribute to the communication process. Likewise, it is necessary for the professional to determine whether the parents or family know about the genetic condition, which will provide an opportunity to correct any misconceptions or alleviate doubts. The answers given by the professional must be communicated clearly and calmly and end with a brief summary of the clinical characteristics of the patient’s condition; in doing so, they must maintain an appropriate balance of information on aspects of the diagnosis that must be considered without providing too much information, as this would be exhausting for both parties. These steps represent a mutual learning process for all parties involved, in which time is an important factor.Considering the different aspects of the genetic entity under study, its symptoms and clinical signs, and complications that may occur, specialist control is required, and therapeutic strategies for interdisciplinary treatment must be developed. All this information must be communicated, which requires commitment from the parents or the patient to prepare themselves for the challenges raised by the genetic diagnosis. The patient’s existing abilities and skills are important positives in instances where psychomotor and intellectual development may be compromised.All communication of genetic diagnoses must be accompanied by timely genetic counseling, either for parents who wish to have more children or for patients who wish to know the risks to their offspring. In clinical genetics, consultations not only involve investigating a genetic diagnosis and genetic counseling, but must also involve monitoring of the patient’s phenotypic evolution, which constitutes an important pillar in the patient’s interdisciplinary management.In this Special Issue, the authors explain the complexity of diagnosing and communicating diagnoses of rare genetic entities, such as Noonan Syndrome, MECP2 duplication syndromes, Nieman-Pick type C disease, Pompe disease, hypohidrotic ectodermal dysplasia, retropharyngeal synovial cell carcinoma, 22q.11.2 deletion syndrome, and Pfeiffer syndrome ,5,6,7,8.


Castanopsis is one of the most common genus of trees in subtropical evergreen broad-leaved forests and tropical monsoon rainforests in China. Castanopsis hainanensis and Castanopsis wenchangensis are endemic to Hainan Island, but they were once confused as the same species due to very similar morphologies. In this study, nuclear microsatellite markers and chloroplast genomes were used to delimit C. hainanensis and C. wenchangensis. The allelic variations of nuclear microsatellites revealed that C. hainanensis and C. wenchangensis were highly genetically differentiated with very limited gene admixture. Both showed higher genetic diversity within populations and lower genetic diversity among populations, and neither had further population genetic structure. Furthermore, C. wenchangensis and C. hainanensis had very different chloroplast genomes. The independent genetic units, very limited gene admixture, different distribution ranges, and distinct habitats all suggest that C. wenchangensis and C. hainanensis are independent species, thus they should be treated as distinct conservation units. Accurately identifying species identities and boundaries is necessary for determining conservation and management units . There iCastanopisis species are dominant trees in subtropical evergreen broad-leaved forests and tropical monsoon rainforests , a= 0.145) . The gen= 0.095) ,20. In tervation ,21. So, C. wenchangensis and C. hainanensis are very different. Although the overall structure of the chloroplast genome is highly conserved, appreciable differences exist between C. wenchangensis and C. hainanensis. For example, different numbers of forward, palindromic, and reverse repeats are detected in the two chloroplast genomes, and the lengths of ndhF and ycf1 genes are not the same in the two species. The total length difference between the chloroplast genomes of C. wenchangensis and C. hainanensis is 229 bp. In a previous study, the difference in chloroplast genome length between Fagaceae species can reach 1336 bp, but the length difference between the two species in Castanopsis (C. echidnocarpa and C. concinna) was only 41 bp [C. wenchangensis and C. hainanensis lead us to believe that they are two different species [Consistent with this conclusion, we discover that the chloroplast genomes of  species .C. hainanensis  is slightly higher than that in C. wenchangensis , suggesting that the two species have similar potential for adapting to environmental changes. Compared with other species in the genus Castanopsis such as C. acuminatissima  [C. sieboldii  [C. hainanensis and C. wenchangensis are relatively low, which may be due to the small geographic range of the two species [C. hainanensis and C. wenchangensis are endemic to Hainan Island, but they have different habitats, indicating that they have precious gene resources and underlying ecological adaptations that are worth investigating more in depth. It is interesting to find that C. hainanensis exhibits a high degree of genetic uniformity rather than highly structured isolated populations, although it has a wider distribution than C. wenchangensis. AMOVA analysis reveals only negligible genetic differences among populations within each species (FST = 0.04 in C. hainanensis and FST = 0.05 in C. wenchangensis). Furthermore, in terms of how genetic variation is partitioned within and among populations, there does not appear to be a difference between C. hainanensis and C. wenchangensis; both show higher genetic diversity within populations and lower genetic diversity among populations, which is in accordance with the general patterns of genetic diversity in tree species [C. hainanensis and C. wenchangensis are independent species.The higher the genetic diversity of a species, the greater its evolutionary potential and ability to adapt to the environment. Such species have a higher probability of long-term survival when environmental conditions change . In this= 0.716)  and C. s species . This is species ,29. This species ,30 and sC. hainanensis and C. wenchangensis were collected on Hainan Island (w/v) agarose gel.A total of 170 individuals from 11 natural populations of n Island ; Table 5Castanopsis and Castanea species [A total of 16 primer pairs of nuclear SSRs  were scr species ,32,33. Q species .R), observed heterozygosity (HO), expected heterozygosity (He), genetic diversity within populations (HS), total genetic diversity (HT), inbreeding coefficient (FIS), and genetic differentiation among populations . Deviations from the Hardy–Weinberg equilibrium (HWE) were tested with 1000 permutations, and nSSRs deviating from HWE were excluded from further analysis.FSTAT 2.9.4  and GenePopulation genetic structure analysis was performed using STRUCTURE 2.3.4 . The lenC. wenchangensis and C. hainanensis each. DNA library construction and Illumina paired-end sequencing were conducted by Nextomics Biosciences (Wuhan). The chloroplast genome was assembled using the software GetOrganelle 1.7.5.3 [Whole genome resequencing was performed for one sample of  1.7.5.3 , and the 1.7.5.3 . Geneiou 1.7.5.3  was used 1.7.5.3 .https://ir-scope.shinyapps.io/irapp/ (accessed on 17 October 2022)) [http://bibiserv.techfak.uni-bielefeld.de/reputer/ (accessed on 29 October 2022)) [The junction sites of the chloroplast genome were visualized with the online program IRscope (r 2022)) . Long rer 2022)) . The parC. hainanensis and C. wenchangensis are endemic to Hainan Island; the former is distributed in the mountainous regions of the central and southern parts of Hainan Island, while the latter is restricted to the coastal lowlands of Wenchang City. They were once confused as the same species due to their very similar morphologies. Furthermore, C. wenchangensis has been wrongly identified because its description in FRPS is not the same as the original publication. Correctly identifying C. hainanensis and C. wenchangensis and determining their genetic diversity and genetic relationships is of great significance for the conservation and sustainable utilization of these two species.C. hainanensis and C. wenchangensis. Based on the nuclear microsatellite variations, we demonstrate that C. hainanensis and C. wenchangensis are distinct clusters that are highly genetically differentiated with very limited genetic admixture; both showed higher genetic diversity within populations and lower genetic diversity among populations, and neither has further population genetic structure. Furthermore, this work allows us to distinguish the two species based on their chloroplast genomes. The independent genetic units, extremely limited genetic admixture, different distribution ranges, and distinct habitats make us believe that C. wenchangensis and C. hainanensis are independent species, thus they should be treated as different conservation units.In this study, we use nuclear microsatellite markers and comparative chloroplast genomes to determine the delimitation between


Genetic diversity is the raw material of evolution, yet the reasons why it varies among species remain poorly understood. While studies at deeper phylogenetic scales point to the influence of life history traits on genetic diversity, it appears to be more affected by population size but less predictable at shallower scales. We used proxies for population size, mutation rate, direct selection, and linked selection to test factors affecting genetic diversity within a diverse assemblage of Neotropical salamanders, which vary widely for these traits. We estimated genetic diversity of noncoding loci using ddRADseq and coding loci using RNAseq for an assemblage of Neotropical salamanders distributed from northern Mexico to Costa Rica. Using ddRADseq loci, we found no significant association with genetic diversity, while for RNAseq data we found that environmental heterogeneity and proxies of population size predict a substantial portion of the variance in genetic diversity across species. Our results indicate that diversity of coding loci may be more predictable than that of noncoding loci, which appears to be mostly unpredictable at shallower phylogenetic scales. Our results suggest that coding loci may be more appropriate for genetic diversity estimates used in conservation planning because of the lack of any association between the variables we used and genetic diversity of noncoding loci. Genetic diversity is the raw material of evolution but varies between species in ways that are not yet fully understood. We used two genomic datasets for Neotropical salamanders to show that while diversity of coding loci is well predicted by population size and environmental heterogeneity, diversity of noncoding loci may be largely unpredictable. Understanding how intraspecific genetic variation differs across species is essential to predict the ability of populations to adapt to novel environmental conditions; genetic divergence plays a key role in most models of speciation and is increasingly being incorporated into conservation planning , which can vary as a result of both species‐specific parameters (variance in reproductive output and sex ratios) and historical demography  and the nearly neutral theory predicts additional diversity in smaller populations due to the balance of selection and drift maintaining slightly deleterious mutations  and genetic diversity for plants  predicted a large proportion of variance in genetic diversity while attributes of geographic range did not  were significant predictors of genetic diversity of transcriptomic loci, while life history attributes and an estimate of current population size were not  and genetic diversity, possibly as a result of a lower density of targets of selection on larger chromosomes  to understand which processes most strongly affect genetic diversity among species. We use an assemblage of Neotropical salamander species  as the reference for mapping with bwa‐mem . Because of differences in median read depth between datasets, we called SNPs at sites with a read depth of at least six for ddRAD and 60 for transcriptomes using a probability threshold of 1e‐06 for both types of loci.For the ddRAD data, we used the Stacks2  for both ddRAD and transcriptome loci for each species by dividing the number of variable sites between two alleles at each locus by the length of the locus. We then calculated median nucleotide diversity for each species across all loci as our estimator of genetic diversity. Finally, we examined correlations of the number of polymorphic loci, genome size, and the number of species in the pool with mean coverage for each species in our ddRAD dataset in order to understand possible technical artifacts related to coverage differences between species that may have affected our results.Because of the large size of the salamander genomes in our dataset and resulting reduction in sequence depth per locus, it is possible that we failed to obtain sequence data for both alleles for some ddRAD loci. Considering that low depth in ddRAD libraries can cause only one of the two alleles to be sequenced, we decided to estimate genetic diversity only from loci with at least one heterozygous site. To generate comparable estimates with transcriptomic data, we estimated genetic diversity from only heterozygous RNASeq loci. We estimated nucleotide diversity (2.3www.gbif.org), using only points with voucher specimens. We checked all points against range maps to eliminate misgeoreferenced specimens or incorrect taxonomic identifications. After quality control, we retained over 30,000 records for the species in our dataset, some of which included more than one specimen. We used the total number of vouchered specimens for each species after quality control as a proxy for population size. We estimated geographic range size by constructing a 10 km buffer around each museum record and merging overlapping buffers for a species. We then summed the total area of all buffered points as an estimate of geographic range size. Values for proxies of population size are given in Appendix We included three proxies of census population size that have been used in prior studies of genetic diversity : Bio4 , Bio16 (precipitation of the wettest quarter), and Bio17 (precipitation of the driest quarter). We calculated the range of the two precipitation variables for each species by subtracting the minimum and maximum values recorded for the species. For microendemic species known from a single site, the range of climatic variables was equal to zero; in these cases, we changed zeros to a very small number (0.001) to avoid undefined values after log transformation of the data. For temperature seasonality, we used the value extracted from the locality used in our molecular dataset.Although our ecological knowledge of most species of bolitoglossine salamanders is limited, a study of temperature selection and thermal variation in their environments showed that while most species select specific temperature ranges, they are often limited by the diversity of thermal environments with sufficient moisture Feder, . The abiBecause we have no estimate of mutation rate for the species in our study, we used mean annual temperature as a proxy for mutation rate following Wright et al. , who shoLissotriton vulgaris  was markedly shorter than the long maps found in Ambystoma mexicanum (Ambystomatidae)  and Notophthalmus viridescens . Plethodontid salamanders, which show the widest variation in genome size within the salamanders, may have as many as three chiasmata per chromosome arm , with homologous chromosomes essentially being scaled versions of each other across species depending on genome size , while we expected to see a positive relationship between these variables and genetic diversity for transcriptomic loci because environmental heterogeneity leads to selection for different alleles across a species range. Finally, we expected to see a negative relationship between genome size and genetic diversity, as larger genomes should have a lower recombination rate per bp and thus stronger linked selection, reducing diversity at linked sites. We summarize the hypothesized relationships between our predictor variables and genetic diversity in Figure Bolitoglossa alberchi, B. nympha, B. odonnelli, B. xibalba, Bradytriton silus, Chiropterotriton mosaueri, Cryptotriton monzoni, and Oedipina uniformis) do not have available genome size estimates and were excluded from initial analyses. Because we did not find a significant effect of genome size on genetic diversity for any subset (see Section We performed model testing separately for three genetic loci/species subsets: (A) heterozygous ddRAD loci, (B) heterozygous transcriptomic loci, and (C) ddRAD and transcriptomic loci for species in common between the two data types (hereafter referred to as the combined dataset). Because we expect most ddRAD loci to be noncoding, and thus less likely to be under direct selection, we compared the results of ddRAD and transcriptomic loci to understand the effects of direct selection on genetic diversity for the two locus types. Possible bias resulting from different species between the two full datasets was tested using the combined dataset. Eight of the species in the ddRAD dataset .Estimates of genetic diversity of bolitoglossine salamander species ranged from pi = .0012–.015 for ddRAD loci and pi = .0020–.0072 for heterozygous transcriptomic loci Figure . For ddRC‐value estimates.For ddRAD loci, no predictor variable was significantly associated with genetic diversity using a simple linear model or a phylogenetic stepwise model in either the full or the combined dataset. This remained true when the analyses were rerun excluding genome size to include the eight species without R2 = .49; Table R2 = .60). Results from ordinary least squares regression were broadly similar to those from phylostep although fewer variables were significant for the combined dataset  and one proxy of effective population size (SVL) are significant predictors of genetic diversity  is the predictor with the most weight for genetic diversity of coding loci, with the range of precipitation in the driest quarter having the second highest summed AIC weight Table . For ddR4We found contrasting results for predictors of genetic diversity for presumably noncoding (ddRAD) and coding loci. For ddRAD loci, no variable was significantly associated with genetic diversity for the full dataset or the set of species in both locus types. For transcriptomic loci, measures of environmental heterogeneity and proxies of population size explained a substantial portion of the variance in genetic diversity across both subsets. These results indicate that genetic diversity of noncoding regions of the genome may be unpredictable at shallower phylogenetic scales, in accordance with the results of Singhal et al. , while dNecturus maculosus  but higher than for Ambystoma opacum and A. talpoideum   vary by about one order of magnitude and fall within the range of those from previous studies that examined genetic diversity of eukaryotes using intergenic regions, introns and fourfold degenerate sites of pi = 0.0001–0.25  rather than to effective population size (Ne), a measure of the strength of genetic drift in a population. Although Nc and Ne should be correlated  under demographic equilibrium conditions, Singhal et al.  or because of differences in methodology and data quality. Likely as a result of the large genome size of all salamanders in this study, our depth of coverage for all ddRAD loci (mean coverage 5×–20× per locus across libraries) was low compared to mean depth of coverage for transcriptomic loci (23×–62×). This, combined with our use of only one individual per species, means that we were unlikely to uncover low‐frequency variants within species. The significant correlation between mean coverage and genome size  was not a significant predictor of genetic diversity estimated for either data type. This could either mean that linked selection does not affect genetic diversity strongly in this group, contrary to the results of Corbett‐Detig et al. , or thatIn contrast to the results for ddRAD loci, the best model for genetic diversity of heterozygous transcriptomic loci shows significant associations of proxies of environmental heterogeneity and population size with genetic diversity. Population size is typically negatively associated with body size, as larger organisms tend to have lower average population density . Our transcriptomic data have substantially higher coverage depth compared to the ddRAD loci, and thus estimates of genetic diversity are likely more accurate for transcriptomic data than for ddRAD data.The large difference in explanatory power and predictors between ddRAD and transcriptomic loci cannot be due to species composition alone, as the combined dataset had no predictor significantly associated with ddRAD genetic diversity while the model for transcriptomic genetic diversity had five predictors and much higher explanatory power  is often used as a proxy for adaptive genetic diversity, which should determine the ability of species to adapt to environmental changes such as climatic warming. The discrepancy between results from our two datasets may mean that, while genetic diversity estimates from noncoding loci are increasingly incorporated in conservation and management strategies, it may be more appropriate to use diversity estimates from coding loci, upon which selection is more likely to act directly. As an alternative strategy, conservation efforts could attempt to protect populations that are likely to maximize genetic variation based on the associations we found. For salamanders, our results suggest that larger species in environments with less variation in dry season precipitation are likely to have the lowest genetic diversity, and thus might struggle to adapt to environmental changes brought by climate change and anthropogenic disturbance. High‐quality whole‐genome data for closely related species, together with linkage maps or recombination estimates across the genome, will provide a stronger test of the impact of mutation, selection, and drift on genetic diversity of wild populations.María Guadalupe Segovia‐Ramírez: Conceptualization ; data curation (lead); formal analysis ; investigation (lead); methodology (lead); writing – original draft . Obed Ramírez‐Sánchez: Formal analysis ; methodology (supporting); writing – review and editing (supporting). Louis Paul Decena Segarra: Data curation (supporting); investigation (supporting); writing – review and editing (supporting). Hairo Rios‐Carlos: Data curation (supporting); investigation (supporting); writing – review and editing (supporting). Sean M. Rovito: Conceptualization ; funding acquisition (lead); investigation (supporting); project administration (lead); writing – original draft .The authors have no conflict of interest to declare.