ارزیابی گوناگونی ژنتیکی در هشت نژاد گوسفند بومی ایران (اویس آریس) با بهره گیری از نشانگرهای ای اف ال پی

This article discusses how associations form professional identities and reflects on the establishment of the Journal of Western Archives. It highlights the ways in which the establishment of the journal is a manifestation of the development of a Western regional archival identity and underscores the role that individuals play in the creation of associational identities. One of the most compelling vignettes in world literature, found in Miguel de Cervantes’ classic novel Don Quijote, deals with the difficulties of establishing identity. In the novel, Don Quijote forges a new identity for himself as a valiant knight errant; he is accompanied by his neighbor Sancho Panza, whom he has made his faithful squire, as he goes on various adventures. In the incident referenced, Quijote and Panza have just come upon thirty or forty windmills. Quijote declares that the windmills are giants and that they must be vanquished before they can cause more misery and suffering. The following conversation, illustrative of the difficulty of forming a new identity, occurs. “What giants?” asked Sancho Panza. “The ones you can see over there,” answered his master, “with the huge arms, some of which are very nearly two leagues long.” “Now look, your grace,” said Sancho, “what you see over there aren’t giants, but windmills, and what seem to be arms are just their sails, that go around in the wind and turn the millstone.” “Obviously,” replied Don Quijote, “you don’t know much about adventures. Those are giants—and if you’re frightened, 1 Daines: Tilting at Windmills Published by DigitalCommons@USU, 2010 take yourself away from here and say your prayers, while I go charging into savage and unequal combat with them.” Quijote, in reality a retired country gentleman named Alonzo Quijano, is clearly deeply invested in the new identity that he is creating for himself, while Sancho Panza is struggling to adapt to his new identity as a faithful squire. Panza is far more comfortable with his former identity as Quijano’s neighbor. Over the course of the novel, Panza comes to accept the new identity that Quijano has created for him and recognize the benefits that this new identity has given him. The process of identity formation is particularly interesting to me, as I have been deeply enmeshed, over the last two decades, in the process of transitioning from an identity of a student studying to enter medical school to the identity of a professional archivist. Identity is composed of various meanings that we and others attach to ourselves. These “meanings, or self-conceptions, are based on the social roles and group memberships a person holds (social identities) as well as the personal and character traits they display, and others attribute to them, based on their conduct (personal identities).” In professional settings, identity development “often involves tailoring one’s identity to a prototypic role identity.” This is a difficult task for archivists working in the United States, as our archival identity is currently in flux. Rand Jimerson has argued that the “most striking feature of the American archival profession in recent years is its ongoing search for identity and for public acceptance as a socially significant profession.” The archival profession’s concern with identity development is not unique. Other professions have also struggled to create cohesive professional identities that are seen as socially significant by the general public. Jimerson identifies three broad manifestations of American archivists’ search for professional identity as “developing internal standards for professional recognition; enhancing the public image of archives and archivists; and strengthening the research and theoretical foundations of the profession.” 1. Miguel de Cervantes Saavedra, Don Quijote: A New Translation, Backgrounds and Contexts, Criticism/ Miguel de Cervantes, trans. Burton Raffel; ed. Diana de Armas Wilson (New York: W. W. Norton, 1999), 43–44. 2. Herminia Ibarra and Jennifer L. Petriglieri, “Identity Work and Play,” Journal of Organizational Change Management 23, no. 1 (2010), 11.

POU1F1 gene controls cell differentiation and animal growth by binding to target DNA promoter sequence, thereby auto-regulating its own expression and expression of growth hormone (GH), prolactin (PRL) and thyroid-stimulating hormone beta sub-unit (TSHβ) genes. Therefore, the exploration of caprine POU1F1 gene polymorphisms may be vital in the formulation of conservation and breed improvement strategies. In this study, POU1F1 gene was characterized for sequence polymorphisms in 366 individuals from two Nigerian goat breeds ((West African Dwarf (WAD) and Red Sokoto (RS)) and one South African goat breed (Kalahari (KR)). The effects of polymorphisms on litter size were investigated using linear mixed model. Two intronic mutations (g.306G>A and g.11236C>T) were identified. However, no significant association was found between the Single Nucleotide Polymorphisms (SNPs) and litter size in the three populations. The genetic distance based on POU1F1 investigated region revealed that the two Nigerian breeds and the South African breed were identical (pairwise genetic distance of 0.00). Phylogenetic tree constructed from the pairwise distance clustered the three breeds into a single clade with the two Nigerian goat breeds having a more recent common ancestor. Structural analysis of the POU1F1 protein confirmed that Pit-Oct-Unc transcription factors domain (POU) and Homeodomain (HOX) domains are conserved in mammals, with several overlapping sub-domains across the same region in all the three populations. We found a subdomain Subfamily of SANT domain or myb/SANT-like domain in Adf-1 (MADF) in goat, cattle, buffalo and camel that has not been reported in mammals

Quantification of the genetic distance between populations is essential in many genetic research programs. Several formulae have been proposed for the estimation of the genetic distance between populations using gene frequency data. Nei’s D has been the most widely used genetic distance measure in different research programs. But the selection of a suitable measure to estimate genetic distance between real-world human populations is a very difficult task. The present study was undertaken to estimate the genetic distance between Barak Valley Muslims (BVM) and other twenty four nations with the ABO blood group gene frequency data using seven different formulae, as well as to estimate the correlation coefficients between distance measures and to work out the regression equations. Seven genetic distance measures namely Nei’s D, Nei’s Nm, La, Nei’s Da, Dc, Re and Nei’s Ne were calculated between BVM and other 24 nations. Correlation coefficients of Nei’s D with other measures were determined to find out which other genetic distance measures were similar to Nei’s D. Linear regression equations of Nei’s D with other distance measures were determined. Nei’s D showed a highly significant (p=0.01) positive correlation with Cavalli-Sforza and Edwards chord distance Dc (0.90), Reynolds Re (0.90), Nei’s Da (0.74) and Nei’s Ne (0.63) but a negative correlation with Nei’s Nm and La. Since Nei’s D had very high positive correlation with Dc and Re distance measures, any one of these measures could be reliably used in genetic analysis instead of all the three measures for estimating genetic distance between populations.

P770 - Holistic approach in the study of population structure based on the analysis of HLA-DRB1, DRB3, DRB4, DRB5, DQA1, DQB1 Polymorphisms (island of KRK, croatia)

Estimation of genetic diversity is an important factor in germplasm conservation and characterization. In rice breeding programs, genetic diversity information on specific regions of genome can be very useful for the application of marker assisted selection (MAS) and for gene mapping. A total of 152 rice lines were considered for breeding programs using microsatellites (SSR) technique. The total number of polymorphic alleles was 206 with an average of 2 alleles per SSR locus. The PIC value for the SSR loci ranged from 0.479 to 0.5 with an average of 0.498. The highest PIC value was observed for primers RM60, RM6832, RM3838 and RM592. RM1, RM237, RM154 and RM84 had the lowest PIC values in a decreasing order. Nei’s gene diversity ranged from 0.479 to 0.5 with an average of 0.498. Using Shannon’s diversity index, a mean genetic diversity of 0.691 was obtained. The lowest diversity was found for RM1, RM237, RM246, RM154 and RM279 in an ascending order and 27 SSR markers had the highest value (0.693). Cluster analysis using the UPGMA method based on Jaccard’s similarity coefficient classified all lines into three clusters. Association analysis by general linear model (GLM) method revealed that 62 SSR markers showed a significant association with 10 studied morphological traits. Twenty eight markers were associated with more than one trait. These may be further investigated in rice breeding programs to be introduced as informative and useful markers. Results showed the potential of SSR markers to identify rice lines at the DNA level. The information will help the selection of lines to serve for efficient rice breeding programs.

For the purpose of the morphometric characterization and differentiation of local sheep breeds that belong to the group of breeds called Pramenka or Zackel, two Slovenian (Bela Krajina and Istrian Pramenka) and four Montenegrin sheep breeds (Bardoka, Sjenička, Pivska Pramenka, and Zeta Žuja) were studied. The variation of morphometric measures and nine morphometric indices were analysed. Principal component analysis (PCA) was applied in order to provide an easier description of body size and shape. Regarding body size, the Sjenička breed was one of the largest breeds (body weight 76.4 kg, wither height 72.7 cm, chest circumference 100.3 cm), while Zeta Žuja had the smallest body size (37.1 kg, 64.8, and 81.9 cm). On the other hand, Slovenian Istrian Pramenka had the largest body length, chest depth, chest width, and rump width among all included breeds (79.4, 33.6, 22.7, and 21.2 cm). Bela Krajina, Istrian Pramenka, and the Sjenička breed, according to the index of body frame (IBF) value (107–114), have a rectangular body frame, Bardoka and Pivska Pramenka have a square body frame (99.3–100), and Zeta Žuja has a short body frame (91.8). The PCA of all morphometric parameters extracted three components accounting for 96.6 % of the cumulative variance. An unweighted pair–group method with arithmetic mean (UPGMA) cluster analysis by Euclidian distance shows diversity among the studied breeds, through it grouped Pivska Pramenka with Sjenička and Istrian with Bela Krajina Pramenka in two clusters, while Bardoka and Zeta Žuja were clustered separately.

This contribution aims to explore some methodological aspects emerged during medical anthropology research with relatives of Huntington’s patients. It also deepens the illness narratives in a help-self groups and art therapy activities, organized by Associazione Italiana per la Corea di Huntington (AICH) of Milan. The field is characterized by exchange of personal experience of illness and disciplinary concepts. Participants and therapists collaborate in the creative process of co-construction of lay knowledge and identity: caregivers, people at genetic risk and therapists highlight different representations and ideas about Huntington’s disease. Therefore, they encourage the creation of new subjectivities. Genetic identity are engendered by the relationship between emotions, experiences and shared knowledge. For this reason, the lateral perspective is necessary to explore the different concepts in a multidisciplinary approaches. In this way, the participant observation put on evidence the production and re-production of nomadic knowledge, that moves concepts and meanings in multiple disciplinary fields.

Multivariate allometric coefficients of red-spot prawn sampled from the adjacent waters of Tashi, Keelung, Taichung and Kaohsiung were estimated and compared to examine whether (1) allometry can be used to elucidate the genetic variation among groups and (2) the assumption that those groups compared share a common allometric pattern in some multivariate statistic method, e. g. Burnaby's method and shearing principal component analysis (PCA) for size correction, or common PCA and multiple-group PCA for multiple-group ordination, can be satisfied. The specimens were sampled during November and December in 1995. A total of 11 measurements was made for each individual. The first eigenvector extracted from the covariance matrix of log-transformed data was used to reflect the multivariate allometric coefficients. The bootstrap method was used to assess the accuracy of estimates. The dendrogram of four areas was constructed by unweighted pair-group method with arithmetic means (UPGMA) by using the angles between four first eigenvectors by sex. The results show that four areas were clustered into two distinct groups for each sex, one group included Tashi, Keelung and Kaohsiung; the other included Taichung. The hypothesis of one common multivariate allometric pattern was clearly rejected. This indicates that some multivariate statistic methods should not be used with out testing this assumption. The geographic clusters are different from the one derived from shape analysis, so the examination in genetic variation among populations by multivariate variate allometric comparison may be not suitable for this species. Different water masses in winter and flow patterns of coastal current around sampling areas may be the main factors to result in the differences of allometric coefficients between two clusters.

At present, registration and protection of rapeseed (Brassica napus L.) cultivars relies on a small number of morphological traits. As the number of cultivars increases, the ability to distinguish them on the basis of these traits becomes more difficult. New descriptors like molecular markers are required to maintain the efficiency of registration testing. The objectives of this study were to (i) evaluate the discrimination power of 17 amplified fragment length polymorphism (AFLP) primer combinations tested on a collection of 83 spring and winter rapeseed cultivars, (ii) assess the structure of the genetic diversity revealed by AFLPs, and (iii) compare three genetic distance estimators (Jaccard, Sokal, and Michener and Sokal and Michener weighted by the PIC). A total of 324 polymorphic markers were scored, with an average of 19.1 markers per primer combination. The use of only two primer combinations was sufficient to identify uniquely all the cultivars. The analysis of the genetic structure of the diversity by cluster and principal component analyses and AMOVAs (analyses of molecular variance) clearly delineated three significant factors: the cultivar type (winter or spring), the country of origin (France or Germany), and the breeding company. The three measures of genetic distance were highly correlated (P < 0.001, r = 0.96–0.98) and led to similar groupings. AFLPs were shown to be a powerful method for identifying cultivars and analyzing the genetic structure of the diversity in rapeseed.

The following supplementary material is available online for this article at http://onlinelibrary.wiley.com/doi/10.1111/jse.12938/suppinfo: Fig. S1. The geographical location of this individual and Records of Empress Wude. Fig. S2. Proportion of C > T and G > A substitutions in human DNA across DNA fragments in the Ashina individual. The red curve represented C > T substitutions that increased at the 5′-end and the blue curve represented G > T substitutions that increased at the 3′-end, as expected for authentic ancient DNA. Fig. S3. Detailed principal component analysis (PCA) of 1667 Eurasian exhibited the west–east Eurasian cline and north–south Eastern Eurasian cline. The Ashina individual fell within present-day and ancient Eastern Eurasians along PC2, and clustered with modern Tungusic and Mongolic speakers, ancient populations in Northeast Asia and eastern Mongolia Plateau, especially the populations previously referred to as "Ancient Northeast Asian" (ANA) that are genetically homogeneous hunter-gatherers from Northeast Asia ("Baikal_EN", 5200–4200 BCE, "Mongolia_N", 6000–4400 BCE, "AR_EN", 5500–5300 BCE, and "DevilsCave_N", 5700 BCE) and post-Iron Age East Steppe nomadic people including Xianbei, Rouran, Khitan and part of Mongols. Fig. S4. ADMIXTURE results for selected Eurasians for K = 2–6. A, Cross-validation (CV) errors for the ADMIXTURE analysis based on 1240 K data set. B, CV errors for the ADMIXTURE analysis based on HO data set. C, ADMIXTURE results for K = 2–6 based on 1240 K data set. After pruning for linkage disequilibrium, the number of SNPs included in this analysis was 871 858, the included modern populations were from HGDP. D, ADMIXTURE results included Turkic populations for K = 2–6 based on HO data set. The number of included SNPs was 279 737. The ADMIXTURE analyses base on 1240 K and HO data set both revealed two summarized ancestries in Ashina: one related to West Eurasian ancestry, the dominating one associated with East Eurasians including ANA and southern ancestry. The results of ADMIXTURE also presented the genetic discrepancy among Ashina, earlyMed_Turk and CentralSteppe_Turk and the genetic heterogeneity among Ashina and present-day Turkic-speaking populations. Fig. S5. Close genetic relationship between ancient and present-day Eurasian populations and geographically different individuals of the Türkic Khaganate. We presented top 60 outgroup-f3 signal for each different group of the Türkic Khaganate. Horizontal bars represent the point estimate ±3 standard error. The outgroup-f3 of Ashina showed the close genetic affinity with East Eurasians than West Eurasians, especially northern East Eurasian. earlyMed_Turk who sampled in Mongolia Plateau presented close genetic relationship with East Eurasians, especially Rouran.The CentralSteppe_Turk harbored similar genetic relationship with Eurasians. Fig. S6. f Statistics in forms of f4 (X, Mbuti; Ashina, pre-Iron Age Northeast Asian populations) and f4 (pre-Iron Age Northeast Asian populations, Mbuti; Ashina, X) test whether pre-Iron Age Northeast Asian populations make contribution to the formation of Ashina. Darker orange and blue squares showed sharing at |Z-score | > 6. Blue and orange squares show sharing at 3 < |Z-score | <6. Gray squares indicate significantly less sharing at the same threshold. A, f4 (X, Mbuti; Ashina, pre-Iron Age Northeast Asian populations) showed Ashina formed a genetic clade together with Neolithic hunter-gatherers in Northeast Asia including Amuer River, Mongolia Plateau and DevilsCave, Baikal Lake (Russia_Shamanka_Eneolithic). In addition, Ashina showed close genetic affinity with population related to Bronze Age SlabGrave and Ulaanzukh culture in Mongolia Plateauwho harbors dominating ANA ancestry. B, f4 (pre-Iron Age Northeast Asian populations, Mbuti; Ashina, X) further provided evidence that ancestry related to hunter-gathers in Northeast Asia dedicated to the gene pool of Ashina as reflected in significantly positive f4 with the exception of Sino-Tibetan populations. Fig. S7. The analysis of f4 (West Eurasian, Mbuti; Ashina, East Eurasian) detected whether gene influx from West Eurasian flowed into the gene pool of Ashina basing on 1240 K data set. A–L, West Eurasians included West Steppe nomadic populations from Bronze Age to Iron Age, Anatolian and Iranian farmers, East hunter-gatherers (EHG), ANE (MA1, Ancient North European) and Botai and the Bactria-Margiana Archaeological Complex (BMAC) of Central Asia. East Eurasian included reported population without gene flow from West Eurasian in previous studies. Different shapes represented different Z-scores of f4. The results showed the gene pool of Ashina was influenced by the eastward migration of West Steppe pastoralists and the population related to BMAC who was attested to migrated along Inner Asia Mountains Corridor into the Mongolia Plateau and influenced ancient Tianshan and Mongolian people (f4 > 0). The detected Anatolia farmers, EHG and Iranian farmers, Botai-related ancestry in Ashina might be mediated by the eastward migration of West Steppe pastoralists and BMAC, respectively. Fig. S8. The significantly genetic heterogeneity within the Türkic Khaganate. A, B, The genetic divergency in individuals of the Türkic Khaganate revealed by f4(X, Mbuti; Ashina, earlyMed_Turk/CentralSteppe_Turk) showing earlyMed_Turk/CentralSteppe_Turk harbored more allele with West Eurasian than Ashina. A, earlyMed_Turk. B, CentralSteppe_Turk. Fig. S9. The genetic relationship of Ashina with Iron-Age Tianshan nomadic populations. A–C, The results of f4 in form of f4 (X, Mbuti; Ashina, Kazakhstan_Kanju/Kazakhstan_Wusun/Kyrgzstan_TianshanHun) all showed Iron-Age Tianshan nomadic people harbored diverse genetic profile with Ashina with more genetic affinity with West Eurasian and West Siberian hunter-gatherers (WSHG). In contrast, Ashina shared more allele with East Eurasians than Iron-Age Tianshan nomadic populations. Different shapes represented different Z-score. Fig. S10. The genetic relationship of Ashina with Xiongnu populations in different periods. Jeong et al. ( 2020) split early Xiongnu into two subgroups, earlyXiongnu_west (SKT010, SKT001, SKT003, SKT009, SKT008, AST001) and earlyXiongnu_rest (JAG001, SKT002, SKT004, SKT005, SKT006, SKT012), based on their individual genetic modeling results. A, B, The results of f4 in form of f4 (X, Mbuti; Ashina, earlyXiongnu_rest/earlyXiongnu_west) showed Ashina shared more genetic affinity with East Eurasians than early Xiongnu. The genetic discrepancy with Ashina was different in earlyXiongnu_rest and earlyXiongnu_west, showing the genetic affinity with ancient populations in Northeast Asia and Mongolia Plateau was similar in earlyXiongnu_rest and Ashina (no significant Z-score). While that genetic profile did not exist in earlyXiongnu_west who harbored more West Eurasian affinity than Ashina. C–E, The results of f4 in form of f4 (X, Mbuti; Ashina, lateXiongnu/lateXiongnu_han/lateXiongnu_sarmatian) presented the difference of harboring genetic relationships with Asina among late Xiongnu: late Xiongnu shared similar genetic affinity to ancient Northeast Asians with Ashina (non-significant Z-score when X included Northeast Asian populations), lateXiongnu_han possessed semblable genetic profile with Ashina (non-significant Z-score, except for AR_EN), that contrasted with lateXiongnu_sarmatian who shared more genetic affinity with West Eurasians than Ashina (significantly negative Z-score when X was West Eurasian populations). Fig. S11. The genetic relationship of Ashina with contemporary East Steppe nomadic populations including Xianbei and Rouran. A–C, The result of f4 in form of f4(X, Mbuti; Ashina, AR_Xianbei_IA/Mongolia_Xianbei/Rouran) revealed the genetic homogeneity of Ashina with Xianbei and Rouran (no significant Z score). Fig. S12. The genetic relationship of Ashina with Mongolic and Tungusic East Steppe pastoralists after the Türkic Khanate. (A–C) The result of f4 in form of f4(X, Mbuti; Ashina, lateMed_Khitan/lateMed_Mongol/Russia_Heishui_Mohe_early_Medieval) demonstrated the discrepancy of genetic relationship with Ashina in Khitan and Mongol empire; Mongolic Khitan and Tungusic Heshui_Mohe had genetic similarity with Ashina, while Mongols in Mongol empir period showed genetic differentiation with Ashina. Fig. S13. The genetic relationship of Ashina with historically Turkic-speaking pastoralists of Central Steppe after the collapse of the Türkic Khaganate. A–E, The result of f4 in form of f4 (X, Mbuti; Ashina, Kimak/KaraKhanid/Uigur/Karluk/Kipchak) indicated the high genetic differentiation between Ashina and later Turkic-speaking pastoralists of Central Steppe including Kimak, KaraKhanid, Uigur, Karluk and Kipchak Khaganate. The Central Steppe pastoralists had evident genetic affinity with West Eurasians (significantly negative Z-score when X included West Eurasians), indicating the prominent ancestry from West Eurasian in the Central Steppe pastoralists, that contrasted with Ashina who harbored dominating ancestry from Northeast Asian. Fig. S14. The genetic relationship of Ashina with Central Steppe pastoralists in Medieval period. A–C, The result of f4 in form of f4(X, Mbuti; Ashina, Kazakhstan_His/Kazakhstan_GoldenHordeAsian/CentralSteppe_Medieval_Nomad) showed diverse genetic relationship with Ashina among Central Steppe pastoralists in Medieval period. Kazakhstan_GoldenHordeAsian formed a genetic clade together with Ashina, which indicating the similar genetic profile between them. However, Kazakhstan_His and CentralSteppe_Medieval_Nomad showed closer genetic affinity with West Eurasians than Ashina. Fig. S15. Genetic heterogeneity of the Türkic Khaganate. Heatmap of P-value of pairwise qpWave among post-Iron Age Central/East Steppe pastoralists. "++" represented values greater than 0.05, and "+" represented values <0.05 and >0.01. Computations were based on the outgroup set (Mbuti.DG + Onge.DG + Russia_MA1_HG.SG + Russia_Kostenki14.SG + Iran_GanjDareh_N + Kazakhstan_Eneolithic_Botai.SG + Russia_Sintashta_MLBA.SG + AR19K + Mongolia_N_North+UpperMid_YR_LN). Fig. S16. The genetic relationship with Ashina of present-day Altaic-speaking populations. A, We conducted f4(X, Mbuti; Ashina, Tungusic/Mongolic/Turkic) to investigate the genetic relationship of present-day Altaic populations with Ashina, and found that Mongolic and Tungusic speakers formed genetic clade with Ashina, and influenced by additional gene flow from millet farmers in Yellow River or West Eurasian in some groups (negative Z-score). By contrast, Turkic populations showed extremely disparate genetic profile with Ashina with the exception of Yakut, Dolgan, Tuvinian and Salar who presented some extent of genetic affinity with Ashina. B, We further performed f4 (Mbuti, Ashina; Tungusic/Mongolic, Turkic) to provide robust evidence of supporting the close genetic affinity with Ashina in Tungusic and Mongolic populations rather than in Turkic populations. Tungusic and Mongolic speakers did have closer genetic relationship with Ashina than Turkic populations (Z < -3). "-"represented −6 < Z-score < −3; "--" represented Z-score < −6; "+" represented 3 < Z-score < 6; "++" represented Z-score >6. C, The result of f4 (Mbuti, Ashina; Tungusic, Mongolic) further revealed Tungusic population shared more alleles with Ashina than Mongolic populations as reflected in significantly negative f4 values with the exception of Eavek_FastEast. Fig. S17. The genetic affinity between Turkic-speaking populations and ancient populations related with the diffusion of Turkic language. Heatmap of P-value of pairwise qpWave among Turkic-speaking populations and ancient populations related with the diffusion of Turkic languages. The genetic relationships between Turkic-speaking population and ancient populations associated with the diffusion of Turkic language revealed the significantly genetic differentiation of Ashina/earlyMed_Turk/earlyXiongnu/lateXiongnu/earlyMed_Uigur and Turkic-speaking populations (P < 0.01), CentralSteppe_Turk formed pairwise clade with Uzbek and Dolgan, the formed pairwise clades existed in other pairwise combination, including pairwise combination of Kimak with Tatar_Siberian, Uyghur, Karakalpak, Nogai_Astrakhan, Nogai_Stavropol and Uzbek, pairwise combination between lateXiongnu to Karakalpak (P > 0.05). "++" represented values >0.05, and "+" represented values <0.05 and >0.01. Computations were based on the outgroup set (Mbuti.DG + Onge.DG + Russia_MA1_HG.SG + Russia_Kostenki14.SG + Iran_GanjDareh_N + Anatolia_N + CHG + AR19K + Mongolia_N_North+UpperMid_YR_LN). Fig. S18. The potential East Eurasian ancestral source of Turkic population. We performed f4(X, Mbuti; Pop, Turkic) to further determine whether other East Eurasians are more suited to explain the East Eurasian ancestry of Turkic than Ashina. X was chosen from representative populations including Chuanyun (the Southern East Asian), YR_LN (millet farmers in Yellow River), Russia_Sintashta_MLBA and Botai. Pop included other potential East Eurasian ancestral source of Turkic-speakers. We observed that Ashina was more suited to approximate East Eurasian ancestry of Turkic populations where Z-scores of f4 (X, Mbuti; Ashina, Turkic) tended to approach to zero. Supplementary Document. Section 1 Archaeological Site and Sample Description of the Xiaoling Mausoleum. Section 2 Material and Methods. Section 3 Ancient Data Analyses and Genetic Characterization of Ancient Individual. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

By Tracey Gendron, M.S. A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University. Virginia Commonwealth University, 2011 Major Director: E. Ayn Welleford, Ph.D. and Barbara J. Myers, Ph.D. Associate Professor and Chair, Gerontology Associate Professor and Director of the Developmental Program, Department of Psychology The growth of the aging population has warranted increased training and education to prepare professionals with the specific knowledge needed to best serve older adults. Gerontology, as an academic discipline, provides professionals with the conceptual knowledge and the skills necessary to address the complexities of working with a diverse aging population. Little research has been done of the characteristics of professionals both with and without formal education in gerontology that are working with the aging population. The aim of this study was to investigate the roles of career motivation, job satisfaction, attitudes about aging, career commitment, and professional identity among those working with older adults. An exploration of the characteristics of gerontological professionals has implications for the development of best practice approaches in student and staff recruitment, retention, curriculum design, and training practices. Participants were recruited from volunteers invited from a convenience sample of approximately 7,000 members signed up to receive emails from the Department of Gerontology at a Southeastern University, and a snowball approach with the link to the survey being distributed by various organizations and institutions (e.g., assisted living facilities, Southern Gerontological Society, Therapeutic Recreation Association). Professionals’ age and job satisfaction significantly predicted professional identity. Participants’ career motivation, job satisfaction, and exposure to formal gerontological education (MSE) significantly predicted career commitment. Self-identified professional identity in aging groups did not moderate the relationship between MSE predictors and career commitment. However, aging anxiety mediated the relationship between job satisfaction and career commitment. Finally, age and higher perception of the value of teamwork predicted both level of professional identity and job satisfaction. This study sheds lights on perspectives of professionals working with older adults and highlights areas for future research and training with this population.

DNA fingerprinting exhibits multilocus genotypes of individuals, detected by the use of a single multilocus probe. Consequently, population data on DNA fingerprinting do not provide a complete characterization of the genetic variation in terms of allele-frequency distributions, since neither the number of loci nor the locus affiliation of alleles is directly observable. Yet DNA fingerprinting has been proved to be a cost-effective method of detecting hypervariable polymorphisms in several organisms, where the traditional loci fail to detect enough variation for microevolutionary studies. In the present paper we demonstrate that the above-mentioned features of DNA fingerprinting data do not cause any serious problem when they are used in evolutionary studies. Bias-corrected estimators of Nei's standard and minimum genetic distances are derived, and, by an application of this theory to data on seven short tandem repeat loci in three major human populations, it is shown that these modified measures of genetic distances based on DNA fingerprint patterns are quite close to Nei's distances based on locus-specific allele frequencies. Empirical as well as theoretical support of the adequacy of such genetic distances from DNA fingerprinting data is also discussed, and it indicates that the technical limitations of DNA fingerprinting should not deter the use of the method for short-term evolutionary studies.

The crocodylid Crocodylus acutus is found in the Central Pacific of Costa Rica only in small populations, and the species is protected by law. RAPD was used to analyze 70 DNA samples of Crocodylus acutus from the rivers Jesus Maria, Tarcoles and Tusubres in the Central Pacific of Costa Rica in order to estimate genetic diversity, differentiation among populations, gene flow and genetic distance between them. Genetic diversity was low in the three rivers, H = 0.2201 in the Jesus Maria river, 0.2358 in the Tarcoles river and 0.2589 in the Tusubres river. Among the three populations there is a metapopulational dynamic (GST = 0.0367), mainly between the populations of the Jesus Maria and Tarcoles rivers. The value of gene flow (Nm = 13.1361) and the number of individuals reported for each river in 2004 suggests that the population of the Tarcoles river is the source and those from Jesus Maria and Tusubres are the drains. There was a direct relationship between the genetic distance and the geographical distance (z = 1.1449, r = 0.9731, p < 0.0010). A conservation strategy for these crocodiles must consider the existence of the metapopulation between the three rivers and the importance of studying the genetics of the American Crocodile in the rest of the Pacific coast of Costa Rica, as well as over the entire distribution range of this species.

Knowledge of the extent and pattern of genetic diversity within and among populations is crucial to identify useful breeding materials and design appropriate collection and conservation strategies. Genetic diversity of 160 durum wheat (Triticum durum Desf) accessions was studied using 15 morpho-agronomic traits. The field studies for morphological characterization were undertaken at Adadi Maryam and Ginchi locations using randomized complete block design with two replications. The average linkage technique of clustering produced a more understandable portrayal of the 160 durum wheat accessions and released varieties by grouping them into seven clusters with inter-cluster D2 values ranged from 13.72 to 235. The highest genetic distances (253) was observed between cluster five (improved varieties) and cluster three accessions. The minimum genetic distance (13.72) was observed between cluster one and two both are landrace collections. Five of the 15 principal components accounted for more than 76.98% of the total variation in the Ethiopian durum wheat genotypes. The first principal components accounted for 32% of the total differences. In this study, there is a moderate genetic diversity between landraces collected from Tigray, Gonder, and Wello. Landraces from these areas can be used as a source of important pre-breeding material for future breeding programs. Key words: Landraces, durum wheat varieties, genetic distances, correlation, genetic diversity, morphological characters.

Maize (Zea mays L.) is a widely cultivated crop in South Africa and forms the main food crop of thousands of rural communities in the country. In order to improve food and nutrition security for marginalised communities, there is need to develop numerous elite quality protein maize (QPM) varieties. The success of a breeding programme is dependent on the existence of molecular variability among the germplasm. The diversity within 45 QPM inbred lines was evaluated using simple sequence repeat markers. Twenty seven simple sequence repeat primers amplified a total of 112 fragments among the inbred lines. The mean polymorphism information content was 0.48, with an average of 4.32 alleles per locus. Cluster analysis using Rogers (1972) genetic distance partitioned the inbred lines into two major clusters with four and nine sub-clusters each. The minimum genetic distances was 0.13 between CIM12 and CIM13, the average genetic distance was 0.32 and the maximum was 0.46. Cross combinations between QS1 and CIM19 and those between QS22 and CIM18 can potentially give substantial heterosis because of the moderate (0.46) genetic distances that were found between them. Hybrids between these parental lines need to be generated and evaluated in yield trials. Key words: Quality protein maize, diversity, inbred lines.