<p>The estimated chicken population of Ethiopia is about 57 million, of which 78.8% are indigenous characterized by low egg production, late maturing and long brooding behavior but celebrated for their hardiness, exceptional scavenging abilities and robust natural immunity against common diseases. The objective of this paper was to review the genetic diversity and improvement interventions of indigenous chicken populations. The review process was started by collecting research articles that were done on genetic diversity and chicken genetic improvement strategies by searching tools such as Google Scholar, PubMed and Web of Science with search terms genetic diversity,&nbsp; genetic characterization and chicken genetic improvement. Lastly, we organized ideas and the write-up was done. Indigenous chicken shows high genetic diversity within the population. The indigenous chickens have high number of alleles (6.25), an effective number of alleles (4.85), observed (55%) and expected (57%) heterozygosity and 90% within-population variation which is considerable variation as unselected African native chickens. Higher heterozygosity levels and considerable genetic variation warranted a further use of ecotypes in improvement through selective breeding. Genetic marker studies showed positive selection signatures of improved from unimproved local chickens. Selective breeding done on Horro chicken breed in Ethiopia saw a remarkable 107.7% and 176.4% improvement in body weight egg number. Uncontrolled dissemination and indiscriminate crossbreeding resulted in the erosion of adaptive local genetic resources. Therefore, improving and conserving indigenous chicken with selective breeding combined with molecular techniques and further studies on the genetic control of productivity traits are very crucial.<br />
&nbsp;</p>


<p>Genetic Diversity of Ethiopian Indigenous Chickens a Base for Sustainable Genetic Improvement: A Review</p>


<p><strong>Background:</strong> Based on D<sup>2</sup> analysis 53 chickpea genotypes were grouped into seven clusters. Among the VII clusters, cluster I consists of 30 genotypes forming the largest cluster followed by cluster II with 16 genotypes, cluster VII with three genotypes and cluster III, IV, V and VI with one genotype each. Inter cluster distance were found to higher than intra cluster distance which depicted wide genetic diversity among the chickpea genotypes under study. Contribution of various characters towards expression of total genetic divergence indicated that seed yield (27.77%) contributed maximum (24.74%) followed by biological yield and number of pods per plant (20.43%). The clustering pattern of genotype demonstrated that clustering does not follow any particular cluster pattern with respect to origin. The pattern of cluster analysis of the first principal component had the largest eigenroot 4.18 per cent of total variation followed by 3.53, 2.91, 2.02, 1.45, 1.26 and 1.15 from second to seven principal components. The eigenroot of first principal component accounted for 19.91 per cent of total variation followed by second to seven principal components which accounted for 16.82, 13.84, 9.62, 6.90, 5.99 and 5.48 per cent of total variations present in the genotypes.<br />
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<strong>Methods: </strong>The study was carried out at Pulses Research Sub-Station (PRSS), Samba and Advanced Center for Rain-fed Agriculture (ACRA), Rakh Dhiansar during <em>Rabi</em> seasons 2017-18 and 2018-19. The experimental material comprising of 48 chickpea (<em>Cicer arietinum</em> L.) genotypes along with 5 checks were evaluated in augmented block design.<br />
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<strong>Result: </strong>The genotypes of cluster II, V and VII had highest inter-cluster distances as well as higher cluster means for most of the yield component traits indicating that these genotypes were most diverse can be used as parents in hybridization programme of chickpea breeding. The variation present in the chickpea genotypes under study can be exploited through selection and hybridization among identified genotypes for breeding high yielding chickpea genotypes.</p>


<p>Genetic Diversity Analysis of Chickpea Genotypes (<em>Cicer arietinum</em> L.) for Seed Yield and Morpho-genetic Traits</p>


<div style="text-align: justify;">Geographical isolation and human interventions resulted in formation of subpopulations among native breeds, which showed differences in morphological or biometric traits. Crossbreeding of indigenous goats with exotic breeds resulted in combining desirable characteristics of many breeds in a composite population. Malabari crossbreds (CB), which had the inheritance of Malabari, Saanen, Alpine and Boer goat breeds were available at University Goat Farm, Mannuthy, Kerala, India. The native goats of Kerala namely, Attappady Black (AB) and populations of Malabari goats from Kannur, Calicut, Thrissur and Malappuram districts (MK, MC, MT and MM) were analysed along with Malabari crossbreds (CB) for genetic diversity. Morphological data were collected from 1776 animals and biometric data from 572 animals representing six goat populations. Qualitative morphological traits analysed were coat colour, presence or absence of horns, tassels, beard, pattern of ear and hair at forequarters and hindquarters. Quantitative biometric traits assessed were chest girth, height at withers, body length and body weight collected from female animals of one to three years of age. Least squares means calculated from SPSS, canonical discriminant analysis by CANDISC, Mahalanobis distance and dendrogram constructed by PROC CLUSTER were used to analyse biometric variables. Canonical discriminant analysis conducted for biometric data identified three statistically significant canonical variables (P&lt;0.0001), with CAN1 explaining 57.2 per cent of total variance. Multivariate analytical techniques thus confirmed the existence of six different populations. The discriminatory capacity of biometric variables chosen for the study was also justified. &nbsp;</div>

<div style="text-align: justify;">Assessment of genetic diversity in goat genetic groups of Kerala, (India) using morphobiometric markers</div>

<p>The aim of this paper was to review the genetic diversities and selection signatures in economical important traits of Ethiopian indigenous cattle. This allows obtaining rapid genetic gain, predicting genomic potential and developing conservation strategies. A genetic variation among Ethiopian breeds ranging from 0.1 to 4.55% and a within variation of 95.45 to 99.9% was reported by various scholars. About 3.51% differentiation between Boran and Fogera from Begait and 2.82% differentiation of Boran from Fogera and Begait was reported. Even though the observed and expected heterozygosity values among Ethiopian cattle population was lower, research reports shown considerably higher values ranging from 0.638&plusmn;0.015 in Boran and 0.714&plusmn;0.022 in Raya-Azebo to 0.700&plusmn; 0.014 in Ambo and 0.735&plusmn;0.017 in Sheko. Genes responsible for heat tolerance, control of metabolic disease, immunity genes, high altitude and low altitude adaptation were reported in Ethiopian cattle breeds. In African indicus and European taurian cattle different genes responsible for milk production, milk fat yield and synthesis and milk composition, were reported. Genes associated with milk traits; fertility and reproduction genes were also reported in Ethiopian cattle. The presence of high within breed variation in Ethiopian cattle creates favorable conditions for further improvement through selection. Beyond identifying candidate potential genes, a detailed study targeting genomic prediction of milk yield and genomic inbreeding had better be done, which allows getting information to optimize and speed up the breeding programs and genetic improvement.</p>


<p>Genetic Diversity and Selection Signatures in Economically Important Traits of Ethiopian Indigenous Cattle Breed as a Base for Dairy Cattle Genetic Improvement: A Review</p>


<div><strong>Background: </strong>The variety of indigenous duck germplasm contribute maximum to the poultry industry in India, besides chicken population. In southern part of India, the available duck genetic resource, particularly Arni ducks (comprises of Sanyasi and Keeri ducks) of Tamil Nadu, has its own characteristics with innate potentiality of higher productivity without any input system of management. Genetic characterization and diversity of indigenous duck genetic resources has not been properly studied. In the present study, the genetic diversity of Arni ducks with other indigenous and exotic duck germplasm were analysed with microsatellite markers.&nbsp;<br />
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<strong>Methods: </strong>Genomic DNA was isolated from the blood samples of six duck populations. Molecular characterization was carried out with duck specific FAO recommended microsatellite markers. The genotyping of ducks was done based on the size of 4324 PCR amplicons of 23 microsatellite loci, which were subjected to capillary electrophoresis using automatic sequencer.<br />
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<strong>Result: </strong>A total of 222 alleles in six duck populations across 23 microsatellite loci with a mean of 9.65&plusmn;0.95 alleles were found. Kuttanad duck variety had the highest number of alleles (139) followed by Sanyasi (136), Keeri (129), Muscovy (118), Assam (91) and White Pekin (78) ducks. The mean observed number of alleles was 6.04&plusmn;0.59, 5.91&plusmn;0.76, 5.61&plusmn;3.17, 5.13&plusmn;0.44, 3.96&plusmn;0.76 and 3.39&plusmn;0.40 in Kuttanad, Sanyasi, Keeri, Muscovy, Assam and White Pekin ducks respectively. The overall mean polymorphism information content (PIC) values among the six duck populations was 0.6269. &nbsp;In most of the duck populations, the mean PIC value was more than 0.5 except in Assam (0.4815) and White Pekin (0.3725) ducks. The observed heterozygosity was the highest in Keeri ducks (0.5217) and lowest in White Pekin ducks (0.2766), while, the mean expected heterozygosity was the highest in Sanyasi (0.5628) and lowest in White Pekin (0.4038) ducks. The variations in the observed and expected number of alleles, differences in PIC of various microsatellite loci might be attributed to the genetic variability of the duck populations, number and type of microsatellite primers utilised for analysis and the genetic diversity of the duck breeds under study. Higher FST value indicates the substantial degree of breed differentiation among the studied duck populations.</div>


<div>Genetic Diversity of Six Duck Populations in India</div>


<p>Genetic diversity of four quail populations, including Korean quails (maroon quails), Peking white quails, Chinese yellow quails and Chinese black quails, were analyzed by microsatellite markers, aiming to provide scientific basis for new breeds of Chinese black quails for egg production as well as the assessment, protection and utilization of Chinese quail&rsquo;s genetic resources. The results showed that 48 alleles were detected by nine microsatellite markers in the four quail populations, with the mean of 5.33 alleles in each locus. The average effective number of alleles marked by the nine microsatellite markers in Chinese black quails, Peking white quails, Chinese yellow quails and maroon quails were 3.5338, 3.6135, 4.0312 and 3.6508 respectively. The average heterozygosity of the four quail populations were 0.6952, 0.7046, 0.7353 and 0.7096 respectively. The average polymorphic information content of nine microsatellite loci in four quail populations were 0.6204, 0.6587, 0.6942 and 0.6639 , respectively, all of which were greater than 0.5, indicating the four populations&rsquo; copious genetic diversity. In this study, the average genetic differentiation coefficient among populations was 0.0349, so the genetic variation among populations accounted for 3.49%, which demonstrated that genetic variation among populations was just a small proportion of the total population genetic variation, and there was little differentiation among the four populations. Cluster analysis indicated that Chinese black quails and Peking white quails were firstly clustered, and then Chinese yellow quails and maroon quails were clustered, and finally the two were clustered together.&nbsp;</p>


<p>Analysis of genetic diversity of four quails by microsatellite markers</p>


<div>Goats are an important domestic animal for animal husbandry that has attracted considerable research attention worldwide. Genetic diversity assessment and population genetic structure of indigenous goats can provide valuable conservation strategies. The current study aimed to evaluate the genetic diversity and population structure of six goat populations from Chongqing, China. A total of 145 animals from five local goat populations, namely, Youzhou black (UZG), Jianzhou (JZG), Banjiao (BJG), Dazu (DZG) and Hechuan white goat (HCG) and an introduced breed called Nubia goat (NBG) located in Chongqing, China were genotyped with 18 autosomal microsatellite markers. A series of genetic diversity parameters and population phylogeny were estimated and constructed. This study preliminarily showed that the six goat populations present rich genetic diversity and significant genetic divergence among them. Furthermore, material exchanges were observed between the introduced and local goat populations in Chongqing. This result will further explain the diversity conservation of Chongqing goat populations.</div>


<p>Genetic Diversity Estimation of Six Goat Populations from Chongqing, China using Microsatellite Markers</p>


<div><strong>Background: </strong>Livestock&nbsp;genetic diversity studies focus on their within and diversity, breed history, adaptive variations, ancestral information, site of domestication and parentage testing and assess the genetic uniformity, admixture or subdivision, inbreeding, or introgression in the population which is helpful in breed formation and their sustainable utilization.<br />
&nbsp;</div>

<div style="text-align:justify"><strong>Methods:</strong> The present research work was conducted during the year 2016-17 at National Bureau of Animal Genetics Resources, Karnal-132001. STR data of 25 markers on 1237 random samples of 27 goat populations was used for analysis. The genetic diversity analysis of new population &nbsp;<em>viz</em>: Narayanpatna, Raighar, Kalahandi, Malkangiri of Odisha state and Rohilkhandi (UK) and their association studies with other Indian goat breeds was performed.<br />
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<strong>Result: </strong>It was found that used markers are highly polymorphic- and the studied breeds/population showed great diversity and distributed mostly on the basis of physio-geographical condition and type of production but among new populations diversity was least which might be due to exchange of animal for breeding purposes. The studied new goat populations were well differentiated from other goat breeds which might be due to physio-geographical condition and breeding practices, so these may be considered as separate breeds/populations. In conclusion, the results showed high level of conserved genetic diversity in the Indian goat breeds. The smaller and isolated new population showed less diversity and a higher inbreeding level as compared to registered breeds.</div>


<div>Genetic Diversity Analysis among 27 Indian Goat Populations using Microsatellite Markers</div>


<div><strong>Background:</strong> The estimation of genetic diversity in pigeonpea is crucial for desiging breeding programmes and germplasm conservation. Morphological studies alone do not provide sufficient information to understand genetic diversity. Molecular analysis using SSRs can provide additional information on genetic diversity that can be used for selection of diverse parents.<br />
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<strong>Methods:</strong> The experimental material for present study consisted of 50 diverse genotypes of pigeonpea. The fifty genotypes were planted in Randomized Complete Block Design consisted of three replications during the <em>kharif</em> 2020-21. The estimation of morphological genetic diversity was done by Mahalanobis D<sup>2</sup> statistics. The molecular genetic diversity analysis was done by using 30 molecular markers in same genotypes.<br />
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<strong>Result:</strong> The assessment of morphological diversity revealed that the fifty pigeonpea genotypes were grouped into four different clusters with cluster I as the largest cluster (33 genotypes). The molecular markers differentiated the 50 genotypes in five major clusters with cluster II as the largest cluster (24 genotypes). The results of present study suggested that morphological and molecular diversity in pigeonpea is different. On the basis of genetic distance, the genotypes RVSA 2014-1 and PA 406 were found most genetically distant and may be used in hybridization programme to create diverse progenies.</div>


<p>Assessment of Morphological and Molecular Genetic Diversity in Pigeonpea [<em>Cajanus cajan</em> (L.) Millspaugh]</p>


<p style="text-align: justify;">Forty nine genotypes of wheat were studied for generating scientific information on nature and magnitude of genetic variability and diversity for designing breeding programme. The experiment was conducted in randomized complete block design in three replications. The data were recorded on days to 50% flowering, plant height, peduncle length, number of productive tillers per plant, days to maturity, spike length, number of spikelets per spike, number of grains per spike, 1000-grain weight, biological yield per plant, grain yield per plant, harvest index and gluten content. &nbsp;Analysis of variance revealed significant differences among the genotypes for all the characters under study. The highest estimates of phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were observed for grain yield per plant. High heritability coupled with high genetic advance was observed for grain yield per plant. Based on D2 &ndash;Statistics, 49 genotypes were grouped into eight clusters. The highest inter-cluster distance was found between cluster VII and VIII followed by III and VII. This indicates that genotypes included in these clusters possess wide genetic diversity. Grain yield per plant (31.46%) showed highest contribution towards genetic divergence; therefore, this character was major determinant of genetic diversity. On the basis of divergence and cluster mean it may be suggested that maximum heterosis and good recombinants could be obtained in crosses between genotypes of cluster VIII, VII and III in varietal improvement programme. Thus, &nbsp;crosses between the genetically diverse genotypes of cluster VIII with genotypes HUW 655, HP 1937, DBW 88 and HD 3058 &nbsp;and cluster VII with genotypes like &nbsp;HP 1938, HUW 656, K1006, DBW83, DBW 84, K1004, UP2822 and NW5050 are expected to exhibit high heterosis and are also likely to produce new recombinants with desired traits.&nbsp;</p>


Genetic Diversity of Ethiopian Indigenous Chickens a Base for Sustainable Genetic Improvement: A Review

Genetic Diversity Analysis of Chickpea Genotypes (Cicer arietinum L.) for Seed Yield and Morpho-genetic Traits

Assessment of genetic diversity in goat genetic groups of Kerala, (India) using morphobiometric markers

Genetic Diversity and Selection Signatures in Economically Important Traits of Ethiopian Indigenous Cattle Breed as a Base for Dairy Cattle Genetic Improvement: A Review

Genetic Diversity of Six Duck Populations in India

Analysis of genetic diversity of four quails by microsatellite markers

Genetic Diversity Estimation of Six Goat Populations from Chongqing, China using Microsatellite Markers

Genetic Diversity Analysis among 27 Indian Goat Populations using Microsatellite Markers

Assessment of Morphological and Molecular Genetic Diversity in Pigeonpea [Cajanus cajan (L.) Millspaugh]

Genetic variability and diversity analysis for yield and its components in wheat (Triticum aestivum L.)