Total Genetic Variation Research Articles

Plant height variation and genetic diversity between Prunus ledebouriana (Schlecht.) YY Yao and Prunus tenella Batsch based on using SSR markers in East Kazakhstan.

Genetic differences between isolated endemic populations of plant species and those with widely known twin species are relevant for conserving the biological diversity of our planet's flora. Prunus ledebouriana (Schlecht.) YY Yao is an endangered and endemic species of shrub almond from central Asia. Few studies have explored this species, which is closely related and morphologically similar to the well-known Prunus tenella Batsch. In this article, we present a comparative analysis of studies of three P. ledebouriana populations and one close population of P. tenella in Eastern Kazakhstan in order to determine the particular geographic mutual replacement of the two species. The populations were collected from different ecological niches, including one steppe population near Ust-Kamenogorsk (P. tenella) and three populations (P. ledebouriana) in the mountainous area. Estimation of plant height using a t-test suggested a statistically significant difference between the populations and the two species (P<0.0001). DNA simple sequence repeat (SSR) markers were applied to study the two species' genetic diversity and population structure. A total of 19 polymorphic SSR loci were analyzed, and the results showed that the population collected in mountainous areas had a lower variation level than steppe populations. The highest level of Nei's genetic diversity index was demonstrated in the 4-UK population (0.622) of P. tenella. The lowest was recorded in population 3-KA (0.461) of P. ledebouriana, collected at the highest altitude of the four populations (2,086 meters above sea level). The total genetic variation of P. ledebouriana was distributed 73% within populations and 27% between populations. STRUCTURE results showed that two morphologically similar species diverged starting at step K=3, with limited population mixing. The results confirmed the morphological and genetic differences between P. tenella and P. ledebouriana and described the level of genetic variation for P. ledebouriana. The study's results proved that the steppe zone and mountain altitude factor between P. tenella and isolated mountain samples of P. ledebouriana.

Estimation of genetic parameters and single-step genome-wide association studies for eating time and rumination time in Holstein dairy cows

The aims of this study were to estimate genetic parameters and to identify genomic regions associated with eating time (ET) and rumination time (RUT) in Holstein dairy cows. Genetic correlations among ET, RUT, and milk yield traits were also estimated. The data were collected from 2019 to 2022 in 6 dairy herds located in the Walloon Region of Belgium. The dataset consisted of daily ET and RUT records on 284 Holstein cows, from which 41 cows had records only for the first parity (P1), 101 cows had records from both the first and second parities, and 142 cows had records only for the second parity (P2). The number of daily ET and RUT records in the P1 and P2 cows were 18,569 (on 142 cows) and 34,464 (on 243 cows), respectively. Data on 28,994 SNPs located on 29 Bos taurus autosomes (BTA) of 747 animals (435 males) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by each 20-SNP sliding window (with an average size of 1.52 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Mean (standard deviation; SD) averaged daily ET and RUT were 327.0 (85.66) and 559.4 (77.69) min/d for cows in P1 and 316.0 (82.24) and 574.2 (75.42) min/d for cows in P2, respectively. Mean (standard deviation; SD) heritability estimates for daily ET and RUT were 0.42 (0.09) and 0.45 (0.06) for cows in P1 and 0.45 (0.04) and 0.43 (0.02) for cows in P2, respectively. Mean (SD) daily genetic correlations between daily ET and RUT were 0.27 (0.07) for P1 and 0.34 (0.08) for P2. Genome-wide association analyses identified 6 genomic regions distributed over 5 chromosomes (BTA1, BTA4, BTA11, 2 regions of BTA14, and BTA17) associated with ET or RUT. The findings of this study increase our preliminary understanding of the genetic background of feeding behavior in dairy cows; however, larger datasets are needed to determine whether ET and RUT might have the potential to be used in selection programs.

Investigating the impact of non-additive genetic effects in the estimation of variance components and genomic predictions for heat tolerance and performance traits in crossbred and purebred pig populations

BackgroundNon-additive genetic effects are often ignored in livestock genetic evaluations. However, fitting them in the models could improve the accuracy of genomic breeding values. Furthermore, non-additive genetic effects contribute to heterosis, which could be optimized through mating designs. Traits related to fitness and adaptation, such as heat tolerance, tend to be more influenced by non-additive genetic effects. In this context, the primary objectives of this study were to estimate variance components and assess the predictive performance of genomic prediction of breeding values based on alternative models and two independent datasets, including performance records from a purebred pig population and heat tolerance indicators recorded in crossbred lactating sows.ResultsIncluding non-additive genetic effects when modelling performance traits in purebred pigs had no effect on the residual variance estimates for most of the traits, but lower additive genetic variances were observed, especially when additive-by-additive epistasis was included in the models. Furthermore, including non-additive genetic effects did not improve the prediction accuracy of genomic breeding values, but there was animal re-ranking across the models. For the heat tolerance indicators recorded in a crossbred population, most traits had small non-additive genetic variance with large standard error estimates. Nevertheless, panting score and hair density presented substantial additive-by-additive epistatic variance. Panting score had an epistatic variance estimate of 0.1379, which accounted for 82.22% of the total genetic variance. For hair density, the epistatic variance estimates ranged from 0.1745 to 0.1845, which represent 64.95–69.59% of the total genetic variance.ConclusionsIncluding non-additive genetic effects in the models did not improve the accuracy of genomic breeding values for performance traits in purebred pigs, but there was substantial re-ranking of selection candidates depending on the model fitted. Except for panting score and hair density, low non-additive genetic variance estimates were observed for heat tolerance indicators in crossbred pigs.

Identification of Superior Haplotypes and Haplotype Combinations for Grain Size- and Weight-Related Genes for Breeding Applications in Rice (Oryza sativa L.).

The identification of superior haplotypes and haplotype combinations is essential for haplotype-based breeding (HBB), which provides selection targets for genomics-assisted breeding. In this study, genotypes of 42 functional genes in rice were analyzed by targeted capture sequencing in a panel of 180 Indica rice accessions. In total, 69 SNPs/Indels in seven genes were detected to be associated with grain length (GL), grain width (GW), ratio of grain length-width (L/W) and thousand-grain weight (TGW) using candidate gene-based association analysis, including BG1 and GS3 for GL, GW5 for GW, BG1 and GW5 for L/W, and AET1, SNAC1, qTGW3, DHD1 and GW5 for TGW. Furthermore, two haplotypes were identified for each of the seven genes according to these associated SNPs/Indels, and the amount of genetic variation explained by different haplotypes ranged from 3.24% to 27.66%. Additionally, three, three and eight haplotype combinations for GL, L/W and TGW explained 25.38%, 5.5% and 22.49% of the total genetic variation for each trait, respectively. Further analysis showed that Minghui63 had the superior haplotype combination Haplotype Combination 4 (HC4) for TGW. The most interesting finding was that some widely used restorer lines derived from Minghui63 also have the superior haplotype combination HC4, and our breeding varieties and lines using the haplotype-specific marker panel also confirmed that the TGW of the lines was much higher than that of their sister lines without HC4, suggesting that TGW-HC4 is the superior haplotype combination for TGW and can be utilized in rice breeding.

Genetska analiza gradskih golubova (Columba livia) kroz markere povezane s bojom perja u općini Montería, Córdoba, Kolumbija

The species known as the domestic pigeon, scientifically Columba livia, has managed to establish itself successfully in urban environments of numerous cities around the world. This expansion has become so significant that it has triggered concerns related to its tendency to nest in human-built structures. This nesting behaviour has contributed to the deterioration of these buildings. The distinctive presence of these birds in neighbourhoods and plazas has generated a growing interest in better understanding the genetic patterns that encode their varied coloration and plumage designs. The aim of this study was to investigate the genetic variability of the population of domestic pigeons (Columba livia) in Montería, Colombia, using phenotypic markers of plumage. Random sampling was conducted between March and April 2023 on 21 flocks of pigeons within the municipality of Montería. Through urban excursions, direct observation, and photographic records, 1570 individuals were phenotypically classified. Autosomal markers encoding coloration and plumage design were studied: Checker (C), Grizzle (G), Spread (S), and Ash-Red (B). The genetic profiles of subpopulations of domestic pigeons were established using the following genetic population indices: expected heterozygosity (He), total genetic diversity (HT), diversity within populations (HS), diversity between populations (DST), coefficient of genetic diversity (GST), gene flow (Nm), and genetic distance between populations. It was found that the most common allele in the studied populations is Checker, allelic frequencies ranged from 0.315 for the Checker gene to 0.005 for the Spread marker. Total genetic diversity was moderate, and genetic differentiation between populations was low, accompanied by a high gene flow. An excess of heterozygotes was also observed, and low genetic distance values were found between populations. The results indicate limited genetic differentiation among populations, leading to the conclusion that pigeon populations in Montería are highly related.

Single-step genome-wide association analyses for milk urea concentration in Walloon Holstein cows

The aims of this study were to conduct a single-step genome-wide association to identify genomic regions associated with milk urea (MU) and to estimate genetic correlations between MU and milk yield (MY), milk composition (calcium content [CC], fat percentage [FP], protein percentage [PP], and casein percentage [CNP]), and cheese-making properties (CMP; coagulation time [CT], curd firmness after 30 min from rennet addition [a30], and titratable acidity [TA]). The used data have been collected from 2015 to 2020 on 78,073 first-parity (485,218 test-day records) and 48,766 second-parity (284,942 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 SNP located on 29 BTA of 6,617 animals (1,712 males) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 kb) was calculated, and the top-3 genomic regions explaining the largest rate of the genetic variance were considered promising regions and used to identify potential candidate genes. Mean (SD) MU was 25.38 (8.02) mg/dL and 25.03 (8.06) mg/dL in the first and second lactation, respectively. Mean heritability estimates for daily MU were 0.21 and 0.23 for the first and second lactation, respectively. The genetic correlations estimated between MU and MY, milk composition, and CMP were quite low (ranged from -0.10 [CC] to 0.10 [TA] and -0.05 [CT] to 0.13 [TA] for the first and second lactations, respectively). The top-3 regions associated with MU were located from 80.61 to 80.74 Mb on BTA6, 103.26 to 103.41 Mb on BTA11, and 1.59 to 2.15 Mb on BTA14. Genes including KCNT1, MROH1, SHARPIN, TSSK5, CPSF1, HSF1, TONSL, DGAT1, SCX, and MAF1 were identified as positional candidate genes for MU. The findings of this study can be used for a better understanding of the genomic architecture underlying MU in Holstein cattle.

Genome-wide scans identify biological and metabolic pathways regulating carcass and meat quality traits in beef cattle

Genome association studies (GWAS) provides knowledge about the genetic architecture of beef-related traits that allow linking the target phenotype to genomic information aiding breeding decision. Thus, the present study aims to uncover the genetic mechanism involved in carcass (REA: rib eye area, BF: backfat thickness, and HCW: hot carcass weight) and meat quality traits (SF: shear-force, MARB: marbling score, and IMF: intramuscular fat content) in Nellore cattle. For this, 6910 young bulls with phenotypic information and 23,859 animals genotyped with 435 k markers were used to perform the weighted single-step GBLUP (WssGBLUP) approach, considering two iterations. The top 10 genomic regions explained 8.13, 11.81, and 9.58% of the additive genetic variance, harboring a total of 119, 143, and 95 positional candidate genes for REA, BF, and HCW, respectively. For meat quality traits, the top 10 windows explained a large proportion of the total genetic variance for SF (14.95%), MARB (17.56%), and IMF (21.41%) surrounding 92, 155, and 111 candidate genes, respectively. Relevant candidate genes (CAST, PLAG1, XKR4, PLAGL2, AQP3/AQP7, MYLK2, WWOX, CARTPT, and PLA2G16) are related to physiological aspects affecting growth, carcass, meat quality, feed intake, and reproductive traits by signaling pathways controlling muscle control, key signal metabolic molecules INS / IGF-1 pathway, lipid metabolism, and adipose tissue development. The GWAS results provided insights into the genetic control of the traits studied and the genes found are potential candidates to be used in the improvement of carcass and meat quality traits.

Functional analysis of recurrent CDC20 promoter variants in human melanoma

Small nucleotide variants in non-coding regions of the genome can alter transcriptional regulation, leading to changes in gene expression which can activate oncogenic gene regulatory networks. Melanoma is heavily burdened by non-coding variants, representing over 99% of total genetic variation, including the well-characterized TERT promoter mutation. However, the compendium of regulatory non-coding variants is likely still functionally under-characterized. We developed a pipeline to identify hotspots, i.e. recurrently mutated regions, in melanoma containing putatively functional non-coding somatic variants that are located within predicted melanoma-specific regulatory regions. We identified hundreds of statistically significant hotspots, including the hotspot containing the TERT promoter variants, and focused on a hotspot in the promoter of CDC20. We found that variants in the promoter of CDC20, which putatively disrupt an ETS motif, lead to lower transcriptional activity in reporter assays. Using CRISPR/Cas9, we generated an indel in the CDC20 promoter in human A375 melanoma cell lines and observed decreased expression of CDC20, changes in migration capabilities, increased growth of xenografts, and an altered transcriptional state previously associated with a more proliferative and less migratory state. Overall, our analysis prioritized several recurrent functional non-coding variants that, through downregulation of CDC20, led to perturbation of key melanoma phenotypes.

Genome-wide association study of early liveweight traits in fat-tailed Akkaraman lambs.

Small ruminants, especially sheep, are essential for sustainable agricultural production systems, future food/nutrition security, and poverty reduction in developing countries. Within developed countries, the ability of sheep to survive on low-quality forage intake could act as buffer against climate change. Besides sheep's importance in sustainable agricultural production, there has been less ongoing work in terms of sheep genetics in Near East, Middle East and in Africa. For lamb meat production, body weight and average daily gain (ADG) until weaning are critical economic traits that affects the profitability of the industry. The current study aims to identify single nucleotide polymorphisms (SNPs) that are significantly associated with pre-weaning growth traits in fat tail Akkaraman lambs using a genome-wide association study (GWAS). A total of 196 Akkaraman lambs were selected for analysis. After quality control, a total of 31,936 SNPs and 146 lambs were used for subsequent analyses. PLINK 1.9 beta software was used for the analyses. Based on Bonferroni-adjusted p-values, one SNP (rs427117280) on chromosome 2 (OAR2) had significant associations with weaning weight at day 90 and ADG from day 0 to day 90, which jointly explains a 0.8% and 0.9% of total genetic variation respectively. The Ovis aries natriuretic peptide C (NPPC) could be considered as a candidate gene for the defined significant associations. The results of the current study will help to increase understanding of the variation in weaning weight and ADG until weaning of Akkaraman lambs and help enhance selection for lambs with improved weaning weight and ADG. However, further investigations are required for the identification of causal variants within the identified genomic regions.

Genetic diversity, variation, and structure of two populations of bigfin reef squid (Sepioteuthis lessoniana d’Orbigny) in Con Dao and Phu Quoc islands, Vietnam

BackgroundBigfin squid is one of the economically important seafood resources in Vietnam’s fisheries and the waters around Con Dao and Phu Quoc islands are two major fishing grounds where this species has been actively exploited. The start codon targeted polymorphism (SCoT) and CAAT box–derived polymorphism (CBDP) techniques were used to generate DNA fingerprinting data to analyze the genetic diversity, variation, and structure of the two populations in the waters surrounding Phu Quoc and Con Dao islands together with mitochondrial cytochrome C oxidase subunit I (COI) gene sequence data. ResultsCon Dao population possessed a higher diversity [expected heterozygosity (He) = 0.2254, Shannon index (I) = 0.3459, percentage of polymorphic bands (PPB) = 80.14%, nucleotide diversity (π) = 0.0336, haplotype diversity (h) = 0.910 with 16 haplotypes] than Phu Quoc population (He = 0.1854, I = 0.2873, PPB = 70.38%, π = 0.0246, h = 0.838 with 14 haplotypes). The genetic diversity at species level in the investigated region was at level of He = 0.2169, I = 0.3399, PPB = 86.41, π = 0.0289, and h = 0.892 with 24 haplotypes. Based on DNA fingerprinting data, the pairwise genetic similarity coefficients among individuals of the Con Dao population were lower (average of 0.7977) than the Phu Quoc population (average of 0.8316). Based on mitochondrial COI data, the pairwise genetic distances among individuals of the Con Dao population were higher (average of 0.0361) than the Phu Quoc population (average of 0.0263). Gene differentiation (GST) between two investigated populations was 0.0316 and 0.0310 leading to the genetic distance was 0.0573 and 0.0213 and the gene flow between them was Nm = 8.2209 and 11.4700 migrants per generation among populations based on DNA fingerprinting and based on COI gene sequence data, respectively. Genetic variation within individuals of both populations (WP) played the key role in total genetic variation at species level in surveyed region. ConclusionsFor the bigfin reef squid species in the surveyed region, the Con Dao population had the higher genetic diversity than the Phu Quoc population, between them existed a low to moderate genetic differentiation and a genetic exchange via gene flow. The DNA fingerprinting data better revealed the genetic differentiation between the two surveyed populations while the mitochondrial COI gene sequence data could show the phylogenetic relationship among the surveyed individuals and the other from the sea regions in Southeast Asia. Based on the results obtained, fisheries management strategies are suggested toward the conservation and sustainable exploitation of this species.

PSXII-3 Including Non-Additive Genetic Effects in Genomic Prediction and Estimation of Variance Components for Performance and Heat Stress Traits in Pigs

Abstract Non-additive genetic effects may have important roles in the phenotypic expression of performance and adaptation traits in livestock. Therefore, we aimed to evaluate the inclusion of non-additive genetic effects in genomic prediction models and variance component estimation of performance traits in a purebred pig population and heat tolerance indicators in a crossbred pig population. The first dataset consisted of 3,534 individuals with genotypes for 52,843 SNPs and five pre-adjusted phenotypes from a public database of a purebred pig line. Twelve models fitting or not dominance and/or epistasis effects (additive-by-additive, additive-by-dominance, and dominance-by-dominance) and inbreeding were used to estimate variance components. Prediction ability was assessed based on 10-fold cross-validation and the bias, dispersion, and accuracy estimates were computed based on the LR method. We also evaluated the impact of including non-additive genetic effects on the ranking of the animals’ breeding value and in the proportion of commonly selected individuals. The second dataset consisted of records from 1,645 lactating sows (Large White x Landrace cross) genotyped for 50,703 SNPs and traits related to heat stress response: skin temperature (ear, shoulder, rump, and tail), vaginal temperature measured every 10 minutes, and the average of the six records per hour corresponding to 08:00, 12:00, 16:00, and 20:00 hours during four days; respiration rate, panting score (PS; score scale from 0 to 3), and hair density (HD, score scale from 0 to 2). Four models including or not, inbreeding and the effect of dominance and additive-by-additive epistasis were used to estimate variance components. There was no effect on residual variance estimates due to the inclusion of non-additive genetic effects in the models for most traits. However, non-additive genetic effects reduced additive variance estimates, especially when additive-by-additive epistasis was fitted. Including non-additive genetic effects in the model did not improve the prediction accuracy of breeding values for purebreds, but there was a substantial change in the ranking of the animals and in the proportion of commonly selected individuals. For the crossbred traits, small non-additive genetic variance with large standard error estimates were obtained. Nevertheless, PS and HD presented notable additive-by-additive epistatic variance. PS presented h2aa estimates of 0.15 and additive-by-additive epistasis corresponding to 86.76% of the total genetic variance, while HD presented additive-by-additive epistatic heritability (h2aa) estimates from 0.46 to 0.49 and the proportion of total genetic variance explained by additive-by-additive epistasis ranged from 66.91% to 71.87%. In conclusion, including non-additive genetic effects did not improve the accuracy of prediction of breeding values for purebreds, but it changed the ranking of animals and selection decisions. Although PS and HD had large additive-by-additive epistasis effects, most of the traits related to heat stress in the crossbred population did not present relevant non-additive genetic effects.

The fragrant orchid &lt;i&gt;Vanilla chamissonis&lt;/i&gt;: an appraisal of the genetic structure of wild populations from Osununú Natural Reserve (Misiones, Argentina)

Due to diverse factors the commercial crops of vanilla are highly vulnerable to genetic erosion. The species Vanilla chamissonis Klotzsch has been shown to produce interesting bioeconomic compounds that could diversify the market. In Argentina, the distribution of this fragrant orchid is restricted to specific north-eastern regions, like the Osununú Natural Reserve (at San Ignacio, Misiones), where it grows wildly in sectors (nuclei). This germplasm represents a locally adapted endemism, and thus is a valuable resource worth preserving. Herein, the genetic characterization of unexplored V. chamissonis´ germplasm was accomplished; as well, the specimens´ molecular identification was assessed in a phylogenetic context using nuclear and chloroplastidial markers. The genotyping exposed that, at least, four gene pools contribute to the genetic diversity of these plants, and that ca. 81% of total genetic variation is allocated within populations. Present results suggest a predominance of sexual reproduction, that population N1 emerges as a candidate unit worth conserving, and that a genetic discontinuity was evidenced between northeastern and southwestern nuclei due to their different genetic constitutions. In concurrence, a tenuous isolation by distance was also unveiled. Our phylogenetic results suggest that it is appropriate to consider the vanilla germplasm surveyed as V. chamissonis. The basic knowledge generated in this work will aid in guiding the in-situ conservation and management initiative, ongoing at the Osununú´s reserve.

Does the definition of a novel environment affect the ability to detect cryptic genetic variation?

Anthropogenic change exposes populations to environments that have been rare or entirely absent from their evolutionary past. Such novel environments are hypothesized to release cryptic genetic variation, a hidden store of variance that can fuel evolution. However, support for this hypothesis is mixed. One possible reason is a lack of clarity in what is meant by 'novel environment', an umbrella term encompassing conditions with potentially contrasting effects on the exposure or concealment of cryptic variation. Here, we use a meta-analysis approach to investigate changes in the total genetic variance of multivariate traits in ancestral versus novel environments. To determine whether the definition of a novel environment could explain the mixed support for a release of cryptic genetic variation, we compared absolute novel environments, those not represented in a population's evolutionary past, to extreme novel environments, those involving frequency or magnitude changes to environments present in a population's ancestry. Despite sufficient statistical power, we detected no broad-scale pattern of increased genetic variance in novel environments, and finding the type of novel environment did not explain any significant variation in effect sizes. When effect sizes were partitioned by experimental design, we found increased genetic variation in studies based on broad-sense measures of variance, and decreased variation in narrow-sense studies, in support of previous research. Therefore, the source of genetic variance, not the definition of a novel environment, was key to understanding environment-dependant genetic variation, highlighting non-additive genetic variance as an important component of cryptic genetic variation and avenue for future research.

Genetic variation of tea plant in Ningde and its adjacent regions revealed by single nucleotide polymorphism genotyping

AbstractNingde (ND), situated in China's prominent tea‐producing region, is recognized as the origin of white tea. It also boasts a wealth of premium tea germplasm resources, which are of vital importance in tea breeding programs. In this investigation, utilizing nanofluidic single nucleotide polymorphisms (SNPs) genotyping technology, the genetic diversity and population structure of tea germplasms sourced from ND and its surrounding regions were scrutinized. A comprehensive collection of 101 tea plant germplasm accessions sourced from ND and its neighboring regions was acquired. Our analysis identified 75 stable and reliable SNP loci that demonstrated the rich genetic diversity of the ND tea germplasms, with an average observed heterozygosity of 0.411 and an expected heterozygosity of 0.382. Notably, the multiple analyses based on high‐quality SNPs revealed that the wild‐type landraces of tea plants in ND are genetically distinct from the cultivars. The analysis of molecular variance results suggested that intrapopulation variation contributed to 79% of the total genetic variation. Moreover, tea plant germplasms in ND interacted with the genetic material of landraces in Nanping and Lishui. Overall, our study provides essential insights into the genetic diversity, relationship, and conservation of ND tea germplasms and lays a molecular basis for innovative utilization and breeding improvement of tea plant germplasms.

Genetic Diversity and Population Structure Analyses in Bitter Gourd (Momordica charantia L.) Based on Agro-Morphological and Microsatellite Markers.

Bitter gourd (Momordica charantia L.) is an important vine crop of the Cucurbitaceae family and is well known for its high nutritional and medicinal values. However, the genetic variation remains largely unknown. Herein, 96 diverse bitter gourd genotypes were undertaken for diversity analysis using 10 quantitative traits, and 82 simple sequence repeat (SSR) markers. Out of 82 SSRs, 33 were polymorphic and the mean polymorphism information content (PIC) value was 0.38. Marker, JY-003 revealed a maximum (0.81) PIC value and, the number of alleles per locus ranged from 2 to 7 (average 3.46). The value of gene diversity showed the presence of a significant level of polymorphism among these genotypes. The unweighted pair group method (UPGMA) cluster analysis grouped the genotypes into two major clusters of which Cluster I comprised mostly small and medium-fruited genotypes of both M. charantia var. charantia and M. charantia var. muricata, whereas Cluster II included mostly long and extra-long fruited genotypes. Furthermore, these genotypes were divided into six distinct groups based on population structure analysis. The diversity analysis based on 10 quantitative traits revealed that earliness and high-yielding ability were exhibited by the predominantly gynoecious line DBGS-21-06 followed by DBGS-48-00. The principal component analysis (PCA) revealed that the first two components exhibited more than 50% of the total genetic variation. The present study deciphered a higher magnitude of agro-morphological and genetic diversity in 96 bitter gourd genotypes. Therefore, trait-specific genotypes identified in this study could be utilized in breeding programmes directed towards the development of improved cultivars and hybrids of bitter gourd.

The marker effects of a single-step random regression model for 4 test-day traits in German Holsteins

The single-step genomic model has become the golden standard for routine evaluation in livestock species, such as Holstein dairy cattle. The single-step genomic model with direct estimation of marker effects has been proven to be efficient in accurately accounting for millions of genotype records. For diverse applications including frequent genomic evaluation updates on a weekly basis, estimates of the marker effects from the single-step evaluations play a central role in genomic prediction. In this study we focused on exploring the marker effect estimates from the single-step evaluation. Phenotypic, genotypic, and pedigree data were taken from the official evaluation for German dairy breeds in April 2021. A multilactation random regression test-day model was applied to more than 242 million test-day records separately for 4 traits: milk, fat, and protein yields, and somatic cell scores (SCS). Approximately one million genotyped Holstein animals were considered in the single-step genomic evaluations including ∼21 million animals in pedigree. Deregressed multiple across-country breeding values of Holstein bulls having daughters outside Germany were integrated into the national test-day data to increase the reliability of genomic breeding values. To assess the stability and bias of the marker effects of the single-step model, test-day records of the last 4 yr were deleted, and the integrated bulls born in the last 4 yr were truncated from the complete phenotypic dataset. Estimates of the marker effects were shown to be highly correlated, with correlations ∼0.9, between the full and truncated evaluations. Regression slope values of the marker-effect estimates from the full on the truncated evaluations were all close to their expected value, being ∼1.03. Calculated using random regression coefficients of the marker effect estimates, drastically different shapes of the genetic lactation curve were seen for 2 markers on chromosome 14 for the 4 test-day traits. The contribution of individual chromosomes to the total additive genetic variances seemed to follow the polygenic inheritance mode for protein yield and SCS. However, chromosome 14 was found to make an exceptionally large contribution to the total additive genetic variance for milk and fat yields because of markers near the major gene DGAT1. For the first lactation test-day traits, we obtained ∼0 correlations of chromosomal direct genomic values between any pair of the chromosomes; no spurious correlations were found in our analysis, thanks to the large reference population. For trait milk yield, chromosomal direct genomic values appeared to have a large variation in the between-lactation correlations among the chromosomes, especially between first and second or third lactations. The optimal features of the random regression test-day model and the single-step marker model allowed us to track the differences in the shapes of genetic lactation curves down to the individual markers. Furthermore, the single-step random regression test-day model enabled us to better understand the inheritance mode of the yield traits and SCS (e.g., variable chromosomal contributions to the total additive genetic variance and to the genetic correlations between lactations).

Use of ISSR markers to assess the genetic diversity of an endemic plant of Morocco (Euphorbia resinifera O. Berg)

BackgroundEuphorbia resinifera is a melliferous, medicinal, and endemic plant to Morocco. Nevertheless, its ecological and genetic diversity still unknown. The objective of this study is to analyze the diversity and genetic structure of Moroccan wild populations of E. resinifera using ISSR markers. Twelve natural populations collected from its geographical range in Morocco were analyzed using 14 ISSR primers. ResultsA total of 125 bands were obtained, with polymorphism of 74.81%. The polymorphic information content (PIC), resolving power (Rp), Shannon’s information index (I), and total genetic diversity (Ht) were 0.33, 2.8, 0.35, and 0.21, respectively. The analysis of molecular variance showed that 75.56% of the total variability is present within populations and that 24.44% exists among populations. Also, the analysis showed a very low genetic differentiation between groups of mountain range type (FCT = 0.066), mountain versant type groups (FCT = −0.024), and altitude groups (FCT = −0.022). Moreover, the geographical distances between populations are correlated with their corresponding genetic distances according to the Mantel test (r = 0.507; P < 0.0001). ConclusionThese results suggest that the population structuring follows a model of isolation by geographical distance. Indeed, the genetic structuring of populations into two groups obtained from PCoA and structure analysis revealed a dependence on the geographical origin of the populations. By contrast, the genetic distances are not correlated with the altitude.

Genetic Diversity of the Endemic Species Phanera sirindhorniae in the Mekong Basin of Thailand Based on ISSR Markers

Phanera sirindhorniae, an endemic species to the Mekong Basin’s upper northeastern region in Thailand, is notable for its therapeutic properties in alleviating pain and discomfort. The objective of this study was to assess the genetic diversity of P. sirindhorniae derived from four natural sources, specifically Sakon Nakhon, Nakhon Phanom, Bueng Kan and Mukdahan provinces, utilizing Inter-Simple Sequence Repeat (ISSR) markers. A total of 51 samples were analyzed, and 10 primers exhibited distinct, robust amplified fragments and polymorphism. The amplified fragment sizes ranged from 170 to 1,300 base pairs, identifying a total of 113 amplified fragments, of which 107 (94.69 %) displayed polymorphism. Polymorphic information content (PIC) values spanned between 0.112 and 0.429, while Nei’s gene diversity ranged from 0.2088 ± 0.2184 to 0.2994 ± 0.1912. Assessment of genetic diversity within and among populations revealed the total genetic diversity (Ht = 0.3443 ± 0.0225) and the genetic diversity within populations (Hs = 0.2617 ± 0.0161). The variability among populations (Gst = 0.2401) indicated a significant degree of gene flow (Nm = 1.580). The Analysis of Molecular Variance (AMOVA) results supported this, with 74 % of genetic differentiation occurring within populations and 26 % among populations. Using the Neighbor-Joining (NJ) generated from Nei’s genetic distance-based clustering analysis, Dendrogram construction successfully classified 2 distinct groups. The analysis revealed that P. sirindhorniae from Nakhon Phanom, and Bueng Kan constituted 1 group, whereas P. sirindhorniae from Mukdahan, and Sakon Nakhon formed another. These findings provide essential data for developing genetic conservation initiatives for this valuable genetic resource. HIGHLIGHTS This study presents the inaugural analysis of genetic diversity in wild Phanera sirindhorniae populations, a species designated as endangered, utilizing Inter-Simple Sequence Repeat (ISSR) markers. A group of 10 Inter Simple Sequence Repeat (ISSR) primers showed values for Polymorphism Information Content (PIC), with (AG)8YC (PIC= 0.445) standing out. These results highlight their potential for use in the investigation of genetic diversity. The examination of P. sirindhorniae resulted in the identification of 2 distinct genetic groups, which have the potential to inform and facilitate the development of genetic conservation strategies for this crucial genetic resource. GRAPHICAL ABSTRACT

Genetic Diversity and Population Structure of Juniperus seravschanica Kom. Collected in Central Asia.

Juniperus seravschanica Kom. is a species that grows widely in the mountain ranges from Central Asia to Oman. It is an important tree for the formation of shrub-forest massifs in mountainous areas and for draining and fixing soils from middle to high altitudes. A comprehensive study of the species' genetic diversity and population structure is a basic approach to understanding the current status of J. seravschanica resources for the development of future conservation strategies. Samples from 15 populations of J. seravschanica were collected from the mountain ranges of Uzbekistan, Kyrgyzstan, and Kazakhstan. The genetic diversity and population structure of 15 Central Asian populations of J. seravschanica were assessed using 11 polymorphic simple sequence repeat (SSR) markers. Genetic diversity parameters, including the number of alleles (na), the effective number of alleles (ne), Shannon's information index (I), the percentage of polymorphic loci (PPL), Nei's genetic diversity index (Nei), principal coordinate analysis (PCoA), etc., were evaluated. The analysis of 15 J. seravschanica populations based on 11 polymorphic SSRs detected 35 alleles. The average PIC value was 0.432, and the highest value (0.662) was found in the JT_40 marker. Nei's genetic diversity index for the J. seravschanica populations was 0.450, ranging from 0.407 (population 14) to 0.566 (population 4). The analysis of molecular variance (AMOVA) showed that 90.3% of total genetic variation is distributed within the population. Using the alleles of all the populations, the gene flow (Nm) was found to be 4.654. Population structure analysis revealed poor clustering in the studied populations and confirmed our AMOVA results. The output of this work can be efficiently used for the maintenance of the species across the Central Asian region.

Incorporating the pedigree information in multi-environment trial analyses for improving common vetch.

Common vetch is one of the most profitable forage legumes due to its versatility in end-use which includes grain, hay, green manure, and silage. Furthermore, common vetch is one of the best crops to rotate with cereals as it can increase soil fertility which results in higher yield in cereal crops. The National Vetch Breeding Program located in South Australia is focused on developing new vetch varieties with higher grain and dry matter yields, better resistance to major diseases, and wider adaptability to Australian cropping environments. As part of this program, a study was conducted with 35 field trials from 2015 to 2021 in South Australia, Western Australia, Victoria, and New South Wales with the objective of determining the best parents for future crosses and the vetch lines with highest commercial value in terms of grain yield production. A total of 392 varieties were evaluated. The individual field trials were combined in a multi-environment trial data, where each trial is identified as an environment. Multiplicative mixed models were used to analyze the data and a factor analytic approach to model the genetic by environment interaction effects. The pedigree of the lines was then assembled and incorporated into the analysis. This approach allowed to partition the total effects into additive and non-additive components. The total and additive genetic effects were inspected across and within environments for broad and specific selections of the lines with the best commercial value and the best parents. Summary measures of overall performance and stability were used to aid with selection of parents. To the best of our knowledge, this is the first study which used the pedigree information to breed common vetch. In this paper, the application of this statistical methodology has been successfully implemented with the inclusion of the pedigree improving the fit of the models to the data with most of the total genetic variation explained by the additive heritable component. The results of this study have shown the importance of including the pedigree information for common vetch breeding programs and have improved the ability of breeders to select superior commercial lines and parents.