Estimates Of Genetic Diversity Research Articles

Predicting milk protein fractions using infrared spectroscopy and a gradient boosting machine for breeding purposes in Holstein cattle

In recent years, increasing attention has been focused on the genetic evaluation of protein fractions in cow milk with the aim of improving milk quality and technological characteristics. In this context, advances in high-throughput phenotyping by Fourier transform infrared (FTIR) spectroscopy offer the opportunity for large-scale, efficient measurement of novel traits that can be exploited in breeding programs as indicator traits. We took milk samples from 2,558 Holstein cows belonging to 38 herds in northern Italy, operating under different production systems. Fourier transform infrared spectra were collected on the same day as milk sampling and stored for subsequent analysis. Two sets of data (i.e., phenotypes and FTIR spectra) collected in 2 different years (2013 and 2019-2020) were compiled. The following traits were assessed using HPLC: true protein, major casein fractions [αS1-casein (CN), αS2-CN, β-CN, κ-CN, and glycosylated-κ-CN], and major whey proteins (β-lactoglobulin and α-lactalbumin), all of which were measured both in grams per liter (g/L) and proportion of total nitrogen (% N). The FTIR predictions were calculated using the gradient boosting machine technique and tested by 3 different cross-validation (CRV) methods. We used the following CRV scenarios: (1) random 10-fold, which randomly split the whole into 10-folds of equal size (9-folds for training and 1-fold for validation); (2) herd/date-out CRV, which assigned 80% of herd/date as the training set with independence of 20% of herd/date assigned as the validation set; (3) forward/backward CRV, which split the data set in training and validation set according with the year of milk sampling (FTIR and gold standard data assessed in 2013 or 2019-2020) using the "old" and "new" databases for training and validation, and vice-versa with independence among them; (4) the CRV for genetic parameters (CRV-gen), where animals without pedigree as assigned as a fixed training population and animals with pedigree information was split in 5-folds, in which 1-fold was assigned to the fixed training population, and 4-folds were assigned to the validation set (independent from the training set). The results (i.e., measures and predictions) of CRV-gen were used to infer the genetic parameters for gold standard laboratory measurements (i.e., proteins assessed with HPLC) and FTIR-based predictions considering the CRV-gen scenario from a bi-trait animal model using single-step genomic BLUP. We found that the prediction accuracies of the gradient boosting machine equations differed according to the way in which the proteins were expressed, achieving higher accuracy when expressed in g/L than when expressed as % N in all CRV scenarios. Concerning the reproducibility of the equations over the different years, the results showed no relevant differences in predictive ability between using "old" data as the training set and "new" data as the validation set and vice-versa. Comparing the additive genetic variance estimates for milk protein fractions between the FTIR predicted and HPLC measures, we found reductions of -19.7% for milk protein fractions expressed in g/L, and -21.19% expressed as % N. Although we found reductions in the heritability estimates, they were small, with values ranging from -1.9 to -7.25% for g/L, and -1.6 to -7.9% for % N. The posterior distributions of the additive genetic correlations (ra) between the FTIR predictions and the laboratory measurements were generally high (>0.8), even when the milk protein fractions were expressed as % N. Our results show the potential of using FTIR predictions in breeding programs as indicator traits for the selection of animals to enhance milk protein fraction contents. We expect acceptable responses to selection due to the high genetic correlations between HPLC measurements and FTIR predictions.

Appraising the Genetic Makeup of an Allochthonous Southern Pike Population: An Opportunity to Predict the Evolution of Introgressive Hybridization in Isolated Populations?

Biological invasions are a major threat to the conservation of biodiversity, as invasive species affect native biota through competition, predation, pathogen introduction, habitat alteration, and hybridisation. The present study focuses on a southern pike population, Esox cisalpinus (Teleostei: Esocidae), that has been introduced outside the species' native range. Using microsatellite markers, this study's objective was to gather baseline genetic information and assess the presence of hybrids between this species and E. lucius in the introduced population. The resulting estimates of genetic diversity and effective population size are comparable to those observed in the species' native range. Although different methods yield contrasting and uncertain evidence regarding introgressive hybridization, the presence of late-generation hybrids cannot be completely ruled out. Large numbers of breeders as well as multiple introductions of genetically divergent cohorts and introgressive hybridisation may explain the high genetic diversity of this recently introduced southern pike population. The present study issues a warning that the conservation of southern pike' introgressive hybridisation between northern and southern pike might be underestimated. The genetic information gathered herein may unravel the origin, number of introduction events, and evolutionary trajectory of the introduced population. This information may help us understand the evolution of introgressive hybridisation in the southern pike's native areas.

Multivariate analysis of selected agro-morphological traits of common wheat genotypes for estimation of genetic diversity

Estimation of genetic diversity of plant species using agro morphological parameters is of very crucial importance in plant improvement programs. In view of that common wheat (Triticum aestivum L.) genotypes consisting of stripe rust resistant genes were analyzed by cluster analysis, principle component analysis and coefficient of correlation analysis for determination of genetic diversity. Experiment was conducted in fields of Hazara University Mansehra Pakistan. Eight groups were categorized by cluster analysis using UPGMA clustering method. AOC-YR/ATTILA (CGSS97Y0061S-23Y-1B-1B) (Sdf31) and 10790 (sdf2) are reported as more diversified by cluster analysis. Based on principal component analysis the first five clusters showed 88.94% of genetic variation. Grains per spike contributed more (0.7) to total variation in PCI. While Harvest Index was the major contributor (0.8) to total variation in PCII. 1056 (Sdf5), AOC-YR/ATTILA (CGSS97Y0061S-32Y-1B-1B) (sdf30), 1072 (sdf6), 1076 (sdf9), and LALBMONO4*4/PRL//LALB (CGSS99Y00093S-2F1-22Y-9GHB-1GHB) (sdf32) were observed superior in flag leaf area, spike length, grains per spike, plant height, biological yield, plant yield and harvest index. AOC-YR/ATTILA (CGSS97Y0061S-32Y-1B-1B) (Sdf30) was found as early maturing genotype. Correlation analysis showed positive and significant association of plant yield with flag leaf area, spike length and biological yield, while it is highly negatively correlated to no. of days to maturity. More diversified genotypes identified in this studies can be used in future breeding programs along with utilization of superior genotypes in hybridization.
 Key words: cluster analysis, correlation, genetic diversity, principal component analysis, whea

Estimation of Genetic Diversity by Principal Component Analysis of Yield Attributing Traits in Katarni Derived Lines

Katarni is a non-basmati traditional aromatic rice cultivar being grown in the Bhagalpur, Banka, and Munger districts of Bihar. However, it is weak-strawed, tall, prone to lodging, and late maturing. Attempt was made to develop a semi-dwarf and early maturing lines of Katarni by crossing with three semi-dwarf high-yielding cultivars and was advanced to F5 generation. In this study, 54 derived lines of Katarni were studied on the basis of 14 morphological traits. Five principal components (PCs) were observed which contributed 70% of cumulative variability and exhibited Eigenvalues> 1. The first PC (23.31%) and the second PC (35.59%) showed a cumulative variation of 63.90%. On the basis of genotype by trait biplot analysis, flag leaf length, plant height, and fragrance were found to be strongly positive. Genotypes biplot study revealed diverse genotypes like KIR-46 KIR-48, KRS-39, KRS-43, KRS-15, KRS-19, KRS-8, KRS-25, and KMTU-52 which can be further exploited for varietal development.

<i>Corrigendum to</i>: White-footed dunnarts (<i>Sminthopsis leucopus</i>) in Queensland’s Wet Tropics, with the description of a new subspecies

A population of white-footed dunnarts (<i>Sminthopsis leucopus</i>) occurs in the Wet Tropics bioregion of tropical north Queensland, Australia separated by about 1800 km from conspecifics in temperate New South Wales, Victoria and Tasmania. We conducted targeted surveys for <i>S. leucopus</i> in north-east Queensland and obtained new records, including the first reported capture of the species in Queensland in 18 years. We assessed the genetic and morphological divergence of the north Queensland population against New South Wales, Victorian and Tasmanian <i>S. leucopus</i>, in conjunction with distribution and habitat differences, to assess whether this isolate should be described as a distinct taxon. Sequencing of the mitochondrial Cytochrome <i>b</i> gene revealed genetic divergence estimates of 2.3–2.8% and 4.3–4.8% between the north Queensland population and <i>S. l. ferruginifrons</i> (Victoria) and <i>S. l. leucopus</i> (Tasmania) respectively. Based on genetic divergence, cranial morphology, differences in habitat, and geographical isolation, we describe the north Queensland population as a new subspecies of <i>Sminthopsis leucopus</i>. We suggest a conservation classification of Endangered given its small distribution, apparent low density, tropical upland location and potential threats, especially related to climate change.

Genetic parameters for fleece uniformity in alpacas.

Fiber diameter is the main selection objective and criterion in alpaca breeding programs, but it can vary across anatomic regions of the animal. As fiber diameter is usually registered from a unique sample from the mid side of the body, fiber diameter variability within fleece is never addressed and phenotypic and genetic differences may exist for fleece uniformity in alpaca populations. The objective of this work was to estimate the genetic parameters of fleece uniformity in an alpaca population. Fiber diameters measured in three different locations were used as repeated records of the same animal and studied for fitting a model that considers heterogeneous the residual variance of the model. Also, the logarithm of the standard deviation of the three measures was used as a measure of the fleece variability. Estimate of the additive genetic variance of the environmental variability was 0.43±0.14, enough high to suggest the existence of wide room to select for fleece uniformity. Genetic correlation of the trait with its environmental variability was 0.76±0.13 showing that fleece uniformity will be indirectly selected when aiming to reduce the fiber diameter. In the light of these parameters, and due to the cost of registering and the cost of opportunity, it looks no worthy to include uniformity as a selection criterion in alpaca breeding programs.

Estimation of Genetic Divergence and Character Association Studies in Local and Exotic Diversity Panels of Soybean (Glycine max L.) Genotypes

The availability of favorable genetic diversity is a thriving vitality for the success of a breeding program. It provides a firm basis of selecting superior breeding lines for the development of high yielding crop genotypes. In this context, present investigation aimed to generate information on genetic divergence and character association in a diversity panel of 123 local and exotic soybean genotypes. Analysis of variance revealed significant response of the evaluated genotypes based on studied attributes. It depicted the probability of selecting desirable soybean genotypes by focusing on character association studies and genetic diversity analysis. Correlation analysis revealed that seed yield per plant showed high positive correlation with 100-seed weight followed by pods per plant and plant height. Furthermore, path coefficient analysis exposed that pods per plant had maximum direct contribution in seed yield per plant followed by 100-seed weight, days to flowering and SPAD measurement. Genotype named “G-10” showed maximum yield per plant followed by 24607, G-52, 24593, Arisoy, 24566, 17426, A-3127, 24570 and 24567. Genetic diversity analysis grouped the evaluated germplasm into 17 clusters. All clusters showed zero intra-cluster variability; while inter-cluster divergence ranged from 9.00 to 91.11. Cluster V showed maximum inter-cluster distance with cluster XII followed by that of between V and VIII. Moreover, cluster IV with superior genotypes (G-10, 24607, 24593 and 24566), VI (17426 and 24567), XIII (24570) and X (Arisoy and G-52) showed above mean values for most of the studied characters. Overall, the results of hybridization between the superior genotypes of these cluster pairs might be useful for soybean breeding with improving agronomic traits and adaptability.

Genetic diversity and structure of Siberian Stone Pine (Pinus sibirica Du Tour) populations

Abstract Siberian stone pine (Pinus sibirica Du Tour) is a key component of the Eurasian boreal forest ecosystems. However, due to the ongoing climatic changes and anthropogenic activities, the habitats of the species are constantly degrading and reducing. To these reasons, exploring the genetic resources of the species and determining the genetic diversity and structure of today’s populations is essential. In this study, we assessed genetic diversity and differentiation in six Siberian stone pine populations from different forest zones in Middle Siberia. Based on seven microsatellite nuclear markers (nSSR), moderate level of genetic diversity (He=0.455) was detected. A population structure analysis divided the six Siberian stone pine populations into two groups. Southernmost populations were distinguished from the others. Analysis of molecular variance (AMOVA) showed that only 2 % of the genetic variation occurred among populations. Our findings suggest that extensive gene flow may prevent genetic differentiation among Siberian stone pine populations. Hence, further genetic diversity estimation with additional loci is needed for crucial insight into the gene pool of Siberian stone pine populations.

Genetic Diversity Estimation of Rice Genotypes based on Morphological and Quality Parameters through Principal Component Analysis

Genetic Diversity Estimation of Rice Genotypes based on Morphological and Quality Parameters through Principal Component Analysis

Estimation of heritability and genetic variability in selected F1 bitter gourd population for yield and its contributing traits

Bitter gourd is one of the potential vegetables that has been clinically proven with several uses due to its medicinal advantages. However, it is less popular than other vegetable crops. Hence, this study was conducted to obtain detailed information on important agronomic traits and determine the pattern of inheritance of morphological traits in bitter gourd. Four F1 populations, P105 × P11, P11 × P92, P92 × P13 and P13 × P92 have been successfully generated from the hybridisation of four genotypes parental lines (P11, P13, P92 and P105). The result of analysis of variance showed that the parents and the F1 populations were significantly different (p < 0.01) in terms of vine length at 90 days after sowing, days of the first harvest after flowering, fruit number, fruit weight, fruit length, fruit girth, flesh thickness and total yield per plant. It also exhibited significantly different (p < 0.05) on days of to first male and female flower appearances. F1 progeny P11 × P92 recorded the highest total yield per plant (5376 g), followed by the parent P92 (4885 g). Positive and significant correlations were observed between total yield per plant and its contributing traits such as fruit weight (r = 0.81), fruit length (r = 0.73), flesh thickness (r = 0.65), fruit girth (r = 0.63), vine length at 90 days after sowing (r = 0.33) and fruit number (r = 0.27). This indicates a higher magnitude of variability for selection with a larger scope of a breeding program in future. The heritability (h 2 ) values ranged from 68.16% for the days of the first harvest after flowering to 99.81% for fruit weight. The highest value of genetic advance (GA) was recorded by the total yield per plant (3220.53%) while the lowest value was displayed by days of the first harvest after flowering (1.35%), respectively. High heritability and GA values indicated that some characteristics could be inherited by the next generation.

Estimation of Heritability and Genetic Variability in Hexaploid Wheat (Triticum aestivum L.)

The field experiment was carried out during Rabi season in 2019-20, 2020-21 at Mata Gujri College, Fatehgarh Sahib’s Experimental Farm,Department of Agriculture. Experimental materials comprising 15 F1s using half diallel mating design involving six parents were grownin randomized block design. High heritability estimates involving broad sense along with high genetic advance as a percent of meanwas observed for number of grain plant-1, harvest index (%), plant height (cm) and grain yield plant-1 (g). The high genotype coefficientof variation (GCV) and phenotype coefficient of variation (PCV) were observed for grain yield/plant and test weight whereas, moderatevalues for PCV and GCV was recorded for no. of spikelets spike-1, no. of grain spike-1, and spike length (cm) indicating prevalence ofgenetic variability, which can successfully be used for improvement of seed yield genetically in wheat.

Numerical Taxonomic analysis for the estimation of Genetic Diversity among some traditional rice (Oryza sativa L.) varieties of West Bengal

The use of numerical taxonomy in plant systematics is crucial because it allows for the improvement of traditional taxonomic data gathered from sources like as morphology, physiology, chemistry, anatomy, and cytology, among others, by utilizing a better and greater number of documented features. It has been determined that it is crucial to keep track of crop genetic resource management dynamics using the fundamental diversity data of traditional crop varieties or landraces. The protection of rice diversity and the use of diversity for rice breeding are strongly tied to the food security of this region because rice is the most significant staple food in South-East Asia. Traditional rice types continue to grow in many indigenous societies despite the relentless advance of modernization, which includes industrialization and land use rules focused on the market. Folk rice varieties are also grown in various areas of West Bengal. The genetic diversity among these traditional or folk types is the only source for future rice enhancement. In this study, many local rice varieties were gathered from various regions of West Bengal, and "richness data" was calculated utilizing this knowledge. Additional data on agro-morphological traits revealed considerable variations between genotypes. Wide variance among the folk rice genotypes was revealed by estimating mean, range, standard deviation, standard error, and coefficient of variation. Following numerical taxonomic analysis, classification of genotypes revealed high genetic diversity among West Bengal's traditional rice varieties. This genetic variety might be utilised in rice breeding, where it is challenging to get access to new technology.

Estimation of Genetic Variance and Heritability of F2 Populations of Corn Plants in Dry Land

This study was aimed to determine the genetic variance of several F2 population traits of maize, broad heritability values and phenotypic correlations between yields and other quantitative traits. The method used is the experimental method. The experiment was designed in a randomized block design, with 6 replications. The number of treatments was 4 populations, namely population F2, Sinta Unram, hybrid NK212 and NK7328. Each population was planted in 4 rows, each consisted of 40 plants. The observed characteristics included plant height, leaf number per plant, leaf angle, ear length, ear diameter, weight of dry ear harvested per plant and yield (dry seed weight per plant). The data were analyzed by simple statistical analysis and analysis of variance at the 5 percent level of significance. The results showed that the genetic variance of plant height, leaf angle, and dry cob weight at harvest per plant population of F2 was higher than that of Sinta Unram's genetic diversity with relatively wide genetic diversity. The genetic variance of leaf number per plant, ear length and ear diameter were also higher than that of Sinta Unram; but the genetic diversity is quite narrow. The genetic diversity of the F2 population's traits is the same as that of Sinta Unram with a broad category. The heritability value of broad meaning classified as high (> 50 %) was obtained on plant height, leave number per plant, ear length, ear diameter, weight of dry ear harvested per plant and yield; while the leaf angle is classified as moderate. Harvested dry cobs weight per plant showed strong phenotypic correlation with yield (0.827); while other properties are classified as very weak to moderate. Improving the yield of the F2 population can be done by indirect mass selection using the weight of harvested dry cobs per plant as the selected trait

Spatial and Temporal Patterns of Genetic Diversity and Structure in Danish Populations of the Alcon Blue Butterfly Phengaris alcon (Denis & Schiffermüller)

Phengaris alcon is an endangered, ant-associated butterfly found, amongst other places, in Denmark, where it has undergone a severe decline during the last century. However, the population genetic consequences of this decline remain unknown. To explore past and current patterns in population structure in relation to the decline, we analyzed DNA microsatellite data from 184 recent and 272 historical P. alcon specimens from 44 spatiotemporal locations in Denmark. We thus generated the most temporally and spatially comprehensive population genetic dataset for P. alcon in Denmark so far. Our results for the Bayesian population assignment of recent samples revealed three major current genetic clusters: western Jutland, northern Jutland, and the island of Læsø. Estimates of genetic diversity showed signs of inbreeding in several extant populations. When including data from museum specimens, only a single locatSion showed a decline in heterozygosity between 1967 and 2021. We suggest that the two distinct clusters in western and northern Jutland indicate two temporally separated Holocene colonizations of Denmark, the latter of which may have been aided by changes in agricultural practice in the late Neolithic period. The unique genetic signature of the Læsø populations may be a result of the admixture of northern Jutland and western Swedish populations.

Генетическое разнообразие домашнего северного оленя по маркерам двух типов

Abstract. The purpose of the study was to evaluate and compare the genetic diversity of populations of domestic reindeer by hereditary polymorphism of proteins and ISSR DNA fragments. Methodology and methods. The polymorphism of proteins and enzymes was studied by electrophoresis in starch and polyacrylamide gels. Polymorphism of ISSR DNA fragments was studied by the standard method of flanking by inverted repetition of microsatellite loci of DNA sites. Data processing and plotting were performed using standard computer programs Gclstats, Genepop, Exsel. Results. According to the transferrin locus (Tf), nine alleles were identified in the deer of the Little-Earth and Big-Earth tundra. Island Kolguev and mainland Chukchi deer have five and seven alleles, respectively. According to the allelic diversity of hepatic esterase (Est-P3) and ISSR DNA fragments, the examined populations did not differ. Judging by the values of the Shannon indices and effective elements, the level of genetic diversity of the Chukchi mainland tundra and Kolguev Island populations was lower than that of the Eastern European tundra mainland populations. Relative to the reindeer of the mainland tundra of Eastern Europe, the Chukchi mainland and Kolguev island populations diverged in opposite directions according to the frequencies of 10 out of 11 ISSR DNA fragments, Est-P3 alleles, as well as rare Tf alleles. Comparison of estimates of genetic diversity by different types of markers in the examined populations using Shannon indices and effective elements gave ambiguous results. Scientific novelty. According to the level of genetic diversity in the time interval of 40–50 years, similar trends in the divergence of the mainland Chukchi and island Kolguev populations relative to the mainland populations of the Little and Big-Earth tundra of Eastern Europe were revealed.

Agro-morphological traits and SSR markers reveal genetic variations in germplasm accessions of Indian mustard – An industrially important oilseed crop

Indian mustard is an economic and highly important industrial oilseed crop. In this study, genetic diversity among 135 Indian mustard germplasm accessions was evaluated using 11 agro-morphological descriptors and 227 SSRs. Morphological characterization of Indian mustard germplasm accessions exhibited a broad range of variation for characters including biological yield (CV = 25.63%), seed yield (CV = 23.23% and 1000-seed weight (CV = 23.14%); whereas traits such as days to maturity (CV = 2.91%) showed lowest degree of variation. Out of 227 SSR markers evaluated, a total of 159 (70.04%) SSRs produced polymorphic products and 68 (29.96%) SSRs resulted into monomorphic amplicons. The polymorphic markers amplified 575 alleles and the number of alleles ranged from 2-7 with 3.61 average number of alleles per locus. SSR markers BRMS-030, Ra2-E11, Ra2-G05, Ni4-G10 and Ol10B11 generated the highest number of alleles (7). SSR marker Ra2-G05 was having the highest allele frequency (0.84), while BRMS-002 was having the lowest major allele frequency (0.33). Polymorphism information content (PIC) values ranged from 0.24-0.61 with an average value of 0.39 per primer pair. Unweighted pair group method with arithmetic mean (UPGMA) cluster analysis based on morphological traits grouped Indian mustard genotypes into three clusters, while two clusters were obtained based on SSR based clustering. Population structure analysis provided a better estimate of genetic diversity and divided all the genotypes into five subpopulations. Genetically diverse accessions identified may be used for hybridization in Indian mustard crop improvement programs in future.

Evaluation of Genetic Diversity in Dog Breeds Using Pedigree and Molecular Analysis: A Review

Domestic dogs are important for many economic and social reasons, and they have become a well-known model species for human disease. According to research, dog breeds exhibit significant levels of inbreeding and genetic diversity loss, decreasing the population’s ability to adapt in certain conditions, and indicating the need of conservation strategies. Before the development of molecular markers, pedigree information was used for genetic diversity management. In recent years, genomic tools are frequently applied for accurate estimation of genetic diversity and improved genetic conservation due to incomplete pedigrees and pedigree errors. The most frequently used molecular markers include PCR-based microsatellite markers (STRs) and DNA sequencing-based single-nucleotide polymorphism markers (SNP). The aim of this review was to highlight genetic diversity studies on dog breeds conducted using pedigree and molecular markers, as well as the importance of genetic diversity conservation in increasing the adaptability and survival of dog breed populations.

A brief history of population genetic research in California and an evaluation of its utility for conservation decision-making.

A recently published macrogenetic dataset of California's flora and fauna, CaliPopGen, comprehensively summarizes population genetic research published between 1985 and 2020. Integrating these genetic data into the requisite "best available science" upon which conservation professionals rely should facilitate the prioritization of populations based on genetic health. We evaluate the extent to which the CaliPopGen Dataset provides genetic diversity estimates that are 1) unbiased, 2) sufficient in quantity, 3) cover entire species' ranges, and 4) include potentially adaptive loci. We identified genetic diversity estimates for 4,462 spatially referenced populations of 432 species, confirming California's rich published history of population genetics research. Most recent studies used microsatellites markers, which have uniquely high levels of variation, and estimates of all genetic metrics varied significantly across marker types. Most studies used less than 10 loci for inferences, rendering parameter estimates potentially unreliable, and covered small spatial extents that include only a fraction of the studied species' California distribution (median 16.3%). In contrast, the ongoing California Conservation Genomics Project (CCGP) aims to cover the full geographical and environmental breadth of each species' occupied habitats, and uses a consistent approach based on whole-genome data. However, the CCGP will sequence only 12% of the number of individuals, and covers only about half the evolutionary diversity, of the CaliPopGen Database. There is clearly a place in the evaluation of the genetic health of California for both approaches going forward, especially if differences among studies can be minimized, and overlap emphasized. A complementary use of both datasets is warranted to inform optimal conservation decision-making. Finally, a synopsis of the available population genetic data for California, all other US states and 241 other countries, allows us to identify states and countries for which meaningful data summaries, such as CaliPopGen, could be collated and others, which have limited published data available and are prime targets for future, empirical work.

Microsatellite Characterization and Panel Selection for Brown Bear (Ursus arctos) Population Assessment.

An assessment of the genetic diversity and structure of a population is essential for designing recovery plans for threatened species. Italy hosts two brown bear populations, Ursus arctos marsicanus (Uam), endemic to the Apennines of central Italy, and Ursus arctos arctos (Uaa), in the Italian Alps. Both populations are endangered and occasionally involved in human-wildlife conflict; thus, detailed management plans have been in place for several decades, including genetic monitoring. Here, we propose a simple cost-effective microsatellite-based protocol for the management of populations with low genetic variation. We sampled 22 Uam and 22 Uaa individuals and analyzed a total of 32 microsatellite loci in order to evaluate their applicability in individual identification. Based on genetic variability estimates, we compared data from four different STR marker sets, to evaluate the optimal settings in long-term monitoring projects. Allelic richness and gene diversity were the highest for the Uaa population, whereas depleted genetic variability was noted for the Uam population, which should be regarded as a conservation priority. Our results identified the most effective STR sets for the estimation of genetic diversity and individual discrimination in Uam (9 loci, PIC 0.45; PID 2.0 × 10-5), and Uaa (12 loci, PIC 0.64; PID 6.9 × 10-11) populations, which can easily be utilized by smaller laboratories to support local governments in regular population monitoring. The method we proposed to select the most variable markers could be adopted for the genetic characterization of other small and isolated populations.

Estimation of genetic variability and identification of regions under selection based on runs of homozygosity in Beijing-You Chickens

The genetic composition of populations is the result of a long-term process of selection and adaptation to specific environments and ecosystems. Runs of homozygosity (ROHs) are homozygous segments of the genome where the 2 haplotypes inherited from the parents are identical. The detection of ROH can be used to describe the genetic variability and quantify the level of inbreeding in an individual. Here, we investigated the occurrence and distribution of ROHs in 40 Beijing-You Chickens from the random breeding population (BJY_C) and 40 Beijing-You Chickens from the intramuscular fat (IMF) selection population (BJY_S). Principal component analysis (PCA) and maximum likelihood (ML) analyses showed that BJY_C was completely separated from the BJY_S. The nucleotide diversity of BJY_C was higher than that of BJY_S, and the decay rate of LD of BJY_C was faster. The ROHs were identified for a total of 7,101 in BJY_C and 9,273 in BJY_S, respectively. The ROH-based inbreeding estimate (FROH) of BJY_C was 0.079, which was significantly lower than that of BJY_S (FROH=0.114). The results were the same as the estimates of the inbreeding coefficients calculated based on homozygosity (FHOM), the correlation between uniting gametes (FUNI), and the genomic relationship matrix (FGRM). Additionally, the distribution and number of ROH islands in chromosomes of BJY_C and BJY_S were significantly different. The ROH islands of BJY_S that included genes associated with lipid metabolism and fat deposition, such as CIDEA and S1PR1, were absent in BJY_C. However, GPR161 was detected in both populations, which is a candidate gene for the formation of the unique five-finger trait in Beijing-You chickens. Our findings contributed to the understanding of the genetic diversity of random or artificially selected populations, and allowed the accurate monitoring of population inbreeding using genomic information, as well as the detection of genomic regions that affect traits under selection.