Syrmaticus humiae), which has suffered a dramatic decline in population over the last three decades across its ranges in the face of heavy exploitation and habitat loss. Twenty-four distinct alleles were found in 73 S. humiae specimens. We found seven shared alleles among four geographical groups as well as six rare MHCIIB alleles. Most individuals displayed between one to five alleles, suggesting that there are at least three MHCIIB loci of the Hume’s pheasant. The dN ⁄ dS ratio at putative antigen-binding sites (ABS) was significantly greater than one, indicating balancing selection is acting on MHCIIB exon 2. Additionally, recombination and gene conversion contributed to generating MHCIIB diversity in the Hume’s pheasant. One to three recombination events and seventy-five significant gene conversion events were observed within the Hume’s pheasant MHCIIB loci. The phylogenetic tree and network analysis revealed that the Hume’s pheasant alleles do not cluster together, but are scattered through the tree or network indicating a trans-species evolutionary mode. These findings revealed the evolution of the Hume’s pheasant MHC after suffering extreme habitat fragmentation.Major histocompatibility complex (MHC) genes are the most polymorphic genes in vertebrates and encode molecules that play a crucial role in pathogen resistance. As a result of their diversity, they have received much attention in the fields of evolutionary and conservation biology. Here, we described the genetic variation of MHC class II B (MHCIIB) exon 2 in a wild population of Hume’s pheasant ( Syrmaticus humiae) is considered an endangered species of the Phasianidae family, found in northeastern India, northern Myanmar, northwestern Thailand and southwestern China [S. humiae is approximately 6,000–15,000 mature individuals [S. humiae appears to be rare [S. humiae may have undergone a range extension [S. humiae is probably declining slowly [S. humiae is undergoing a decline across many of its ranges, due to heavy exploitation and habitat loss over the last three decades [S. humiae is listed as a Grade I National Protected Wildlife in China [S. humiae collected from Guangxi and Guizhou Provinces did not display lower genetic diversity or significant genetic differentiation. Using RAPD (random amplified polymorphic DNA) methods to investigate a captive population of S. humiae, the results indicated relatively higher genetic diversity and differentiation in the captive population [The Hume’s pheasant  genes are the most polymorphic loci in the vertebrate nuclear genome , and plaS. humiae, which includes amino acid residues contained within the antigen-binding sites (ABS) of the MHC class II molecule [S. humiae, and (ii) whether there is evidence of balancing selection as revealed by phylogenetic analysis, gene conversion and analysis of non-synonymous to synonymous substitution ratios.In this study, we test genetic variation of part of exon 2 of the MHCIIB gene of molecule . We focuS. humiae is listed as Grade I National Protected Wildlife in China, and has small a population size. Therefore, most specimens came from nature reserves and local residents. Due to an edict preventing further specimen collection, specimens from local residents who had preserved tail sections prior to S. humiae being listed as a protected species were utilized. Muscle tissues were obtained from the preserved sections. Blood samples were obtained by trapping. S. humiae specimens were immediately released after the blood samples were collected. The Natural History Museum of Guangxi, Yulin Normal University, and Guangxi Normal University provided ethical approval for this study.Sampling was approved by the Forestry Administration of Guangxi Zhuang Autonomous Region, Jinzhongshan National Nature Reserve, Guzhang Forestry Center, Longtan Nature Reserve. S. humiae samples from Guangxi and Guizhou Provinces, China. Seventy-three wild individuals were obtained from six localities: Longlin County (n = 3), Xilin County (n = 2), Tianlin County (n = 22), Leye County (n = 13), Tian’e County (n = 24) and Luodian County (n = 9)  . Among tS. humiae, we aligned seven related Phasianidae species, Syrmaticus reevesii (GenBank accession no.: JQ001778), Phasianus colchicus , Gallus gallus (HQ203710), Chrysolophus amherstiae (JQ001777), Chrysolophus pictus (JQ440366), Crossoptilon auritum  and Crossoptilon crossoptilon (JQ001779), and designed one new primer pair in conserved regions . The primer pair was situated at the borders of MHCIIB exon 2, of which the amplified region corresponded to amino acids 21 to 91 of β chain of human MHC class II HLA-DR [2, 0.2 mM of each dNTP in a final volume of 50µL. The thermal profile consisted of 5 min at 94°C, followed by 34 cycles at 94°C for 30s, 62°C for 40s, and 72°C for 30s, with a final 8 min extension at 72°C. PCR products were puriﬁed on a 1.5% agarose gel and the band corresponding to the ampliﬁed product isolated with QIAGEN QIAquick Gel Extraction Kit according to the manufacturer’s protocol. Purified PCR products were cloned into the pMD-18T vector (Takara) following manufacturer’s instructions. Fifteen to twenty clones were checked for the correct sized PCR product of 222 bp. After checking, at least 12 correctly sized products were sequenced for each individual using ABI 3730 DNA analyzer .In order to obtain MHCIIB exon 2 of http://blast.ncbi.nlm.nih.gov/Blast.cgi) from NCBI. A new sequence variant was considered as an allele when it met the criteria summarized by Kennedy et al. [π) were calculated using the program DnaSP 5.0 [dN) and synonymous (dS) substitution for each coding region.All sequences were verified through homology with publicized MHCIIB alleles of other species using BLASTN , adding a third site class to M1a, with ω2 > 1. M7 (β) with beta distribution approximating dN ⁄ dS variation; M8 (β & ω) with a proportion of sites evolving with dN ⁄ dS > 1. The topology used in the CODEML analysis was constructed in MEGA 5, using the neighbor-joining (NJ) method with Kimura’s two-parameter evolutionary distances. Conﬁdence for the topology was evaluated using 1000 bootstrapped replicates. M1a vs. M2a and M7 vs. M8 were used to form two pairs of likelihood ratio tests (LRTs) for which the twice log likelihood difference (2△InL) was compared to the x2 distribution to determine the better-fit models. If the selection models (M2a and M8) were significantly better than the neutral models (M1a and M7), we used Bayesian statistics  integrated in CODEML to identify codon sites under balancing selection [Based on the codon-based approaches, we calculated four models: M1a , assuming two site classes, with 0 < ωelection .p value was lower than 0.05 [Recombination events were detected using RDP 3.44 with default selections of RAP, GENECONV and MaxChi methods . Gene cohan 0.05 .http://phylobench.vital-it.ch/raxml-bb/) [Fulica atra) (GenBank accession no.: KF924779)[In order to assess phylogenetic relationships of MHCIIB and MHCIIY in galliform species, fifteen available MHCIIB sequences and four available MHCIIY sequences were downloaded from the GenBank . Phylogexml-bb/)  with 100KF924779) was usedKF924779) and emplKF924779) with JukKF924779).S. humiae  were sequenced and 24 distinct nucleotide variants of MHCIIB exon 2 were identified according to the criteria summarized by Kennedy et al. [Gallus gallus, DAB for Phasianus colchicus [Syhu-DAB*01–24 (GenBank accession no.: KJ817332-KJ817355) according to the nomenclature of Klein et al. [Syhu-DAB sequences were of 222 bp length without stop codons and indels. The 222 bp nucleotide sequences exhibited high polymorphism with 84 variable nucleotide sites. Pairwise sequence divergence among alleles ranged from 0.5% to 30.1%, with a mean of 16.8%. Average nucleotide diversity was π = 0.14291, and the average number of nucleotide differences among alleles was k = 31.72. Amino acid alignment yielded 39 variable codons out of 74 total codons examined. The number of amino acid differences per site (p distance) ranged from 0 to 40.5%, with a mean of 23.1%. Following the three-dimensional structure of the human class II antigen [π) was 2.7 times higher at ABS (0.270) than the non-ABS (0.098).The primers successfully amplified the target fragment in all 73 individuals. Total 1046 clones derived from genomic DNA of 73 y et al. . Becauseolchicus , we simpn et al.  regardle antigen , the 74 S. humiae individuals, 10 displayed one allele (13.7%), 24 displayed two alleles (32.9%), 28 displayed three alleles (38.3%), 6 displayed four alleles (8.2%), 4 displayed five alleles (5.5%), and only one displayed seven alleles (1.3%), with a mean of 2.6 . The rarest allele, Syhu-DAB*23–24 was only detected in a single individual (Syhu32).Individuals displayed between one to seven variants. Of the 73 n of 2.6 . The mosDAB alleles  (Syhu-DAB*22) and Group 3  (Seven -DAB*11)  were sha-DAB*24) .ω (dN ⁄ dS) were 0.921 in the overall MHCIIB exon 2 region, 1.109 in the ABS, and 0.803 in the non-ABS. Based on the Z-test of balancing selection, although these differences were not significant for all sites, ABS and non-ABS, non-synonymous substitutions per site for ABS sites outnumbered the synonymous substitutions per site, suggesting balancing selection at the ABS . The likelihood ratio test of hypotheses showed statistically significant values , revealing the balancing selection model is a better fit to the data compared to other models. Under M2a model, ten codons were identified as being under balancing selection   (The maximum likelihood estimates of parameters under random-site models of variable ability) . Under Mability) . Seven oability) .Sites inferred under selection at the 99% level are listed in bold, and those inferred at the 95% level are shown in italics, underlined sites correspond to the ABS residues in humans. Number of sites is corresponding to that of HLA-DRB specified by Brown et al. .S. humiae MHCIIB locus (Syhu-DAB12 and Syhu-DAB24).The RDP, GENECONV and MaxChi methods of recombination detection found one, three and one recombination events respectively, indicating that recombination or gene conversion events have occurred at MHCIIB exon 2. Seventy-five significant gene conversion events were observed within the IB locus . ConversS. humiae were embedded within MHCIIB group . Following a strict cloning criterion, one individual (Syhu63) in our test possessed up to seven distinct variations. Due to just one individual having more than five alleles and the remaining individuals having less than five alleles, we suggested that there were at least three MHCIIB loci of S. humiae from this study. Similar results have been reported in some galliform species such as Coturnix japonica (7 loci), Gallus gallus (2 loci), Meleagris gallopavo (3 loci), Pavo cristatus (3 loci), Phasianus colchicus (3 loci), Tympanuchus cupido (4 loci), Perdix perdix (2 loci) [S. humiae populations have higher allelic diversity. For instance, ten alleles were identified in the captive red jungle fowl  population of 80 individuals [Perdix perdix) [Fulica atra) [Tetrao tetrix) [Tympanuchus cupido) [S. humiae population declining in numerical abundance and geographic range, neutral markers  displayed relatively high genetic diversity and lacked striking genetic differentiation [S. humiae populations have suffered severe declines in the wild since the 1980s [S. humiae is growing [S. humiae is commonly assumed to be high [S. humiae population.In this study, we have characterized MHCIIB exon 2 variation in a wild population of criteria , twenty-(2 loci) , 38–44. ividuals , twelve  perdix) , two hunca atra) , sixteen tetrix) , and twe cupido) . Despitehe 1980s , 6. Howe growing . Additio be high . Thus, nSyhu-DAB*01" was the most frequent among individuals . This suggests that Syhu-DAB*01 may have been favored by selection in the S. humiae population, probably because of its important role in the immune response against pathogens, adapting to environments or for demographic reasons. Among four geographical groups, we found seven shared alleles  showed statistically significant values (P < 0.001), suggesting a balancing selection model is a better fit to the data compared to other models. Thus, our results indicated that the MHCIIB exon 2 of S. humiae has been the target of balancing selection. Under the BEB analysis, ten sites  in M2a and eleven sites  in M8 have been confirmed to be subject to balancing selection with high ω values  or by more recent gene duplication [The phylogenetic tree and network indicated a pattern of MHCIIB trans-species evolution among galliform species, in agreement with the previous studies , 44. Thelication .S1 Fig(TIF)Click here for additional data file.S1 Table(DOC)Click here for additional data file.S2 Table(DOC)Click here for additional data file.S3 Table(DOC)Click here for additional data file.


IT) was 0.545, population differentiation index (FST) was 0.440, and the global inbreeding of individuals within breed (FIS) was 0.187. The phylogenetic relationships of chickens were examined using neighbor-joining trees constructed at the level of breeds and individual samples. The neighbor-joining tree constructed at breed level revealed two main clusters, with Hedemorahöna and Öländsk dvärghöna breeds in one cluster, and Gotlandshöna and Svarthöna breeds in the second cluster leaving the Skånsk blommehöna in the middle. Based on the results of the STRUCTURE analysis, the most likely number of clustering of the five breeds was at K = 4, with Hedemorahöna, Gotlandshöna and Svarthöna breeds forming their own distinct clusters, while Öländsk dvärghöna and Skånsk blommehöna breeds clustered together. Losses in the overall genetic diversity of local Swedish chickens due to breeds extinction varied from -1.46% to -6.723%. The results of the current study can be used as baseline genetic information for genetic conservation program, for instance, to control inbreeding and to implement further genetic studies in local Swedish chickens.This study aimed at investigating the genetic diversity, relationship and population structure of 110 local Swedish chickens derived from five breeds  using 24 microsatellite markers. In total, one hundred thirteen alleles were detected in all populations, with a mean of 4.7 alleles per locus. For the five chicken breeds, the observed and expected heterozygosity ranged from 0.225 to 0.408 and from 0.231 to 0.515, with the lowest scores for the Svarthöna and the highest scores for the Skånsk blommehöna breeds, respectively. Similarly, the average within breed molecular kinship varied from 0.496 to 0.745, showing high coancestry, with Skånsk blommehöna having the lowest and Svarthöna the highest coancestry. Furthermore, all breeds showed significant deviations from Hardy-Weinberg expectations. Across the five breeds, the global heterozygosity deficit (F Intensive selection and crossbreeding in selected chicken breeds have been practiced over a long time  and has Today there are eleven local Swedish chicken breeds present. Most of the local breeds became threatened by extinction when the commercially international breeds became more common. Typically, only one or few populations with a small number of chickens remained when the Swedish association for local poultry (Svenska Lanthönsklubben) rescued them. The association is still working on maintaining the local chickens in the form of live gene bank. Studies on local Swedish chickens are limited. One breed was included in a study of dermal hyperpigmentation . The mtDCurrently, microsatellite loci are the method of choice to study the genetic diversities within and between populations because they are highly polymorphic, show co-dominant inheritance, found to be abundant and evenly distributed throughout the genome , 10, 11.i) provides us with more insight about the differences and similarities between breeds, ii) can be used as a basic input for future improvement of breeds and to implement effective breed conservation program. This study aimed at investigating the genetic diversity, genetic relationship and population structure of five local Swedish chicken breeds using 24 microsatellite markers.The present study used data obtained from five of the eleven local Swedish chicken breeds. Since these breeds originate from different parts of Sweden  and haveBlood samples were obtained from 110 local Swedish chickens derived from five breeds: Gotlandshöna , Hedemorahöna , Öländsk dvärghöna , Skånsk blommehöna  and Bohuslän-Dals svarthöna (mentioned throughout the paper with its common name Svarthöna) . Chickens were sampled from members of the Swedish association for local poultry. The samples were taken by visits to the owners of the birds or taken by a local veterinarian. Ethical permission was obtained prior to the sampling (see ethics statement below). Gotlandshöna originate from two farms on the island Fårö close to the island Gotland in the Baltic sea. Hedemorahöna originate from one flock in the area close to Hedemora in the county Dalarna. Öländsk dvärghöna originates from two villages on the north part of the island Öland in the Baltic sea. Skånsk blommehöna originate from three villages in the middle part of the county Skåne in southern Sweden. Svarthöna originate from northern Bohuslän in western Sweden (close to the Norwegian border). Genomic DNA for each sample was extracted using QIAamp DNA Blood Midi Kit . DNA from some samples were prepared manually and from some it was prepared with the QIASymphony robot.Ethical permission (number C247/6) for the collection of blood samples was obtained from the Uppsala ethical board for animal research  prior to the collection of samples.Twenty-four microsatellite loci were used to assess the DNA polymorphism. All of the markers are part of the 30 microsatellites recommended by the International Society of Animal Genetics (ISAG)-FAO to study the genetic diversity of chickens .2, dNTPs (25 mM), QIAGEN HotStar Tag (5 U/μl), distilled water, fluorescently labeled forward and unlabeled reverse primers each with 10 μM concentration and genomic DNA (25 ng/μl). Amplification using the thermo-cycler ABI9700 was carried out with an initial incubation and enzyme activation of 95° for 5 min., followed by 35 cycles of denaturation at 90° for 30 sec., primer annealing at 55° for 45 sec. and extension of 72° for 30 sec. and lastly a final extension of 72° for 15 min. After amplification, fragment analysis was conducted using 3500xL genetic analyzer (Applied BioSystems). The GeneMapper 5 computer Software package (Applied BioSystems) was used to determine the fragment sizes and allele calling by comparing with known internal size standard.Polymerase chain reaction (PCR) amplifications were performed based on multiplex PCR techniques using the QIAGEN hot star enzyme  and we optimized the multiplexes manually. The 24 microsatellite markers were grouped into six multiplexes each with three to five pairs of primers per reaction plate. A final volume of 10 μl multiplex PCR master-mix contained: 10x PCR buffer with MgClIT, FST and FIS) were computed according to Weir and Cockerham  was the standard deviation of the estimated log likelihood.The most likely number of clusters  per locus across the five breeds are depicted in IT) was significantly high (P<0.001). Fixation index of subpopulation in relation to the total population (FST) per locus varied from 0.079 at MCW0248 to 0.891 at MCW0104 locus, with the mean being 0.440 (P<0.001). This indicates that about 44% of the total genetic variation in local Swedish chicken population is explained by between breed differences. Nineteen of the 24 loci contributed significantly to the genetic differentiation among breeds. The mean FST in the present study was approximately equivalent to mean FST values of 0.437 and 0.429 reported by Zanetti et al. [et al. [IS value, across the 24 loci was 0.187 (P<0.001). This shows about one-third of the global heterozygosity reduction was due to the within breed deficit. Nine markers revealed significant deficit of heterozygosity, but only three loci  showed excess of heterozygosity , molecular markers can be used instead of pedigrees to access kinship between individuals. Ideally, if a large proportion of the birds in a breed are genotyped, the decision of purchasing of a new breeding animal to a flock can be based on the molecular kinship, so that an animal that have low molecular coancestry to the existing animals in the flock is chosen. Furthermore, sustainable breed conservation program requires huge resources to be invested over long period. Therefore, on top of microsatellite loci based information, breed evaluation for conservation should address other issues such as adaptability of breeds, economic importance and social values of the breeds , 40.In conclusion, the five local Swedish chicken breeds showed low within breed genetic diversity but considerable variations exist between breeds. Relatively high molecular coancestry observed within breeds could potentially increase the level of inbreeding in subsequent generations. Thus, our results highlighted the importance of implementing effective breeding strategies, for example designing breeding programs and applying mating based on minimum molecular coancestry, to prevent further losses in genetic diversity.S1 File(XLSX)Click here for additional data file.


Cynomys parvidens), listed as threatened under the United States Endangered Species Act, was the subject of an extensive eradication program throughout its range during the 20th century. Eradication campaigns, habitat destruction/fragmentation/conversion, and epizootic outbreaks  have reduced prairie dog numbers from an estimated 95,000 individuals in the 1920s to approximately 14,000 (estimated adult spring count) today. As a result of these anthropogenic actions, the species is now found in small isolated sets of subpopulations. We characterized the levels of genetic diversity and population genetic structure using 10 neutral nuclear microsatellite loci for twelve populations (native and transplanted) representative of the three management designated “recovery units,” found in three distinct biogeographic regions, sampled across the species' range. The results indicate (1) low levels of genetic diversity within colonies , (2) high levels of genetic differentiation among colonies , (3) very small genetic effective population sizes, and (4) evidence of genetic bottlenecks. The genetic data reveal additional subdivision such that colonies within recovery units do not form single genotype clusters consistent with recovery unit boundaries. Genotype cluster membership support historical gene flow among colonies in the easternmost West Desert Recovery Unit with the westernmost Pausaugunt colonies and among the eastern Pausaugunt colonies and the Awapa Recovery unit to the north. In order to maintain the long‐term viability of the species, there needs to be an increased focus on maintaining suitable habitat between groups of existing populations that can act as connective corridors. The location of future translocation sites should be located in areas that will maximize connectivity, leading to maintenance of genetic variation and evolutionary potential.The Utah prairie dog ( Puma concolor; Ernest et al. Ceratotherium simum; Nielsen et al. Pteromys volans; Lampila et al. Spermophilus citellus; Ben Slimen et al. Microcebus spp.; Olivieri et al. Cyprinodon diabolis; Martin et al. Etheostoma akatulo; Robinson et al. Habitat loss and range reduction are among the most serious threats to species persistence  guidelines for within ESUs, however they are defined, management practices include reestablishing extirpated populations with individuals from the closest intact populations , where fixation of deleterious alleles and inbreeding depression warranted interbreeding between subspecies , where there were no outbred populations to draw upon, reciprocal translocations between inbred populations were used to genetically rescue this species  designated, the challenge is not only to maintain the coadapted gene complexes which are thought to define each unit, but also to maximize the species‐level genetic diversity in the face of declining population numbers. ESUs have been defined in a number of ways including Moritz's  reciprocCynomys gunnisoni; white‐tailed prairie dog, C. leucurus; black‐tailed prairie dog, C. ludovianus; Mexican prairie dog, C. mexicanus and Utah prairie dog, C. parvidens) were the target of extensive poisoning regimes in the 19th and 20th centuries. These species were thought to be competitors for forage with open range livestock, and their extensive burrow systems were deemed an injury risk for cattle. Ironically, recent research shows that cattle preferentially graze along prairie dog colony edges and use their colony centers for resting, similar to the mutualistic relationship prairie dogs once had with the American bison .As a result of extermination campaigns, many of these once widespread species are either candidates for listing or are now federal or state listed as threatened or endangered: Franklin's ground squirrel Yersinia pestis) introduced into North America in 1899 dramatically reduced the number of individuals. In the 1920s, the number of Utah prairie dog was estimated at ~95,000 individuals, but by the 1960s the population had been reduced substantially and was estimated at <3300 individuals occupying 37 colonies in 1972 , ground squirrels (Spermophilus spp.), and mustelids  . An increase in individuals on private land allowed the species to be reclassified as threatened on May 29, 1984 [United States Fish and Wildlife Service (USFWS) Ne) within colonies and recovery units, and characterized genetic divergence among colonies and recovery units.The objectives of this study were to (1) determine the level of genetic variation retained within this species at neutral nuclear microsatellite loci, (2) compare the levels of genetic variation within native colonies to colonies comprised of transplanted individuals, and (3) assess population genetic structure within and among designated “recovery units.” We assessed the levels of genetic diversity at 10 dinucleotide nuclear microsatellite loci. We used a Bayesian genotype clustering approach to define distinct genetic groups. We also tested for genetic bottlenecks, estimated effective population sizes , access to colonies and by the need for colonies to be sufficient size to trap a target goal of 25–30 individuals per site. Sites were selected to incorporate colonies from each of the three recovery units as well as urban and nonurban sites.The three recognized recovery units are separated by what may represent biogeographic barriers  Fig. . Such laDesignation of the three recovery units was based on the concept of representation, redundancy, and resiliency. Representation refers to spatially capturing the ecological elements of the species across its entire range to ensure the species' adaptive capabilities are conserved. The three recovery units encompass current and historical population and habitat distributions including sufficient habitat coverage in order to provide connectivity among colonies.A scientific collection permit for trapping and tissue collection was obtained from the USFWS (#TE074705) and an Institutional Animal Care and Use (IACUC) protocol approved by Syracuse University IACUC committee. We used Tomahawk live traps baited with sweet feed and/or peanut butter/apple mix to capture individual prairie dogs. Traps were set at active burrow entrances and included multiple coteries within a colony. We calculated relatedness among adults and juveniles per colony to assess sampling of family groups (see below). Ear tissue (5–10 mg) was collected from trapped animals using an 8 mm ear notcher. Tissue samples were frozen at –20 and –80°C upon return to the laboratory from the field. Reproductive status, weight, and age class were recorded at time of capture. Spatial data were collected using a GPS unit (Garmin Etrex Venture), and waypoints were collected around the trapping area in each colony sampled. Utah prairie dogs were trapped 6/27 – 8/12 in 2003 and 6/25 – 8/4 in 2004.Spermophilus columbians), Stevens et al. Spermophilus brunneus brunneus), May et al. Tamias amoenus), Schulte‐Hostedde et al. No microsatellite markers were available for this species; therefore, we used microsatellite loci developed for other sciurids which successfully amplified in the Utah prairie dog . GS12, GS26, IGS6, EAM35, and EAM163 were amplified with 33 cycles of 94°C for 30 sec, followed by annealing temperatures of 60°C  and 59°C  for 90 sec, then a 30 sec extension at 72°C, followed by a 30‐min extension at 62°C. Betaine (3 μL) and BSA (0.6 μL) were added to the IGS1 reaction mix to decrease stutter. PCR amplification for IGS1 was carried out in 15 μL volumes containing 15–20 ng of DNA, one unit of 50× Titanium Taq DNA polymerase , 0.2 μm of forward and reverse primer, 10× titanium Taq buffer, 0.3 mm dNTPs, Betaine (3 μL), and BSA (0.6 μL) and was brought to final volume with ddH20. IGS1 was amplified using two‐step PCR with 33 cycles of 95°C for 30 sec, an annealing temperature of 68°C for 90 sec, then an extension at 72°C for 30 sec, followed by a 30‐min extension at 72°C. PCR amplification for GS14, GS17, GS20, and GS22 was carried out in 15 μL volumes containing 15–20 ng of DNA, one unit of 50× Titanium Taq DNA polymerase , 0.2 μm forward and reverse primer, 10× titanium Taq buffer, and 0.3 mm dNTPs and brought to final volume with ddH20. Loci GS14, GS17, GS20, and GS22 were amplified with 33 cycles of 94°C for 30 sec, an annealing temperature of 56°C , 66°C (GS20), and 64°C (GS22) for 30 sec, then an extension at 72°C for 30 sec, followed by a 30‐min extension at 72°C. Fragment analysis of the PCR products was carried on an Applied Biosystems 3730 genetic analyzer at the Nevada Genomics Center (http://www.ag.unr.edu/genomics/), at the appropriate dilution of PCR product. The genotypes were scored using the program Genemapper v. 3.7., where bins were created using known allele sizes for the microsatellites from the literature with additional bins for novel variation found in the Utah prairie dog.DNA was isolated from ear tissue using Qiagen DNeasy Tissue kits  and quantified using a Labsystems Fluoroskan Ascent fluorometer. PCR amplification was performed using a MBS Satellite 0.2G thermocycler (Thermo Electron Corporation). PCR amplification for GS12, GS26, IGS6, EAM35, and EAM163 was carried out in 15 He), number of alleles (A) and allelic richness per locus per colony (RS), and per locus over all colonies (RT). Observed heterozygosity (Ho) per locus and over all loci was calculated using Microsatellite toolkit in Excel. Observed and expected levels of heterozygosity were compared between native and transplant populations using two‐tailed Mann–Whitney U tests.We used FSTAT  for the six native colonies (1–10) and 1–12 k for all colonies combined. We specified a 500,000 burn‐in period followed by five 1,000,000 MCMC replicates per k to approximate posterior allelic distributions against which individual genotypes were compared and assigned to a cluster  between each pair of k and k−1 for all tests of k. In BAPs, we specified 10,000 input iterations for admixture analysis and ran 10,000 input iterations specifying both 9 and 30 reference individuals per sampling location. We conducted five replicates per k for k = 1–20.Recent comparisons among multiple Bayesian clustering techniques suggest that datasets should be analyzed using multiple methods, which together should support a biologically meaningful pattern  among individuals within each colony using the Lynch and Ritland  was calculated for each colony and genotype cluster using NeEstimator (version 1.3)  from 307 individuals: 33 Adult males, 49 adult females, 116 juvenile males, and 109 juvenile females  for adults only (N = 82), juveniles (N = 223) and for adults and juveniles (N = 307) combined. We found no statistically significant differences in either parameter among groups . Allelic richness was low with ≤5 alleles per locus across all colonies and ranged from 2 to 5 alleles per locus for all 10 microsatellite loci and all colonies combined  and from 1 to 3 alleles per locus per colony  . Many loci were monomorphic in multiple colonies. The average He and Ho values over all loci per recovery unit were as follows (adults and juveniles combined); Awapa = 0.283 (SD ± 0.188) and 0.22 (SD ± 0.299), Paunsaugunt = 0.254 (SD ± 0.197) and 0.229 (SD ± 0.329) and West Desert = 0.190 (SD ± 0.168) and 0.167 (SD ± 0.304). Observed and expected heterozygosities did not differ between native and transplant populations .There was no evidence of allelic dropout for any locus in any population/colony. There was evidence for null alleles at two loci, GS20 and EAM35, in one and two colonies respectively, but there were no systematic pattern of null alleles at any locus across all colonies. We compared genetic diversity and allelic richness . For juveniles, FIS ranged from −1 to 0.495 and three of the four same loci were monomorphic for the same allele in the majority of colonies . However, there was only one significant FIS value among adults and three among juveniles within colonies , which suggests random mating among genetically depauperate individuals.Colony relatedness was high with mean ies Fig. . Based uThe Bayesian genotype clustering results for adults analyzed separately and for all adults and juveniles combined did not differ so we report on the combined analyses here.N = 5 runs per k; Figs Three genotype clusters were identified among the native colonies using STRUCTURE [Avg LnP(D) = −876.04, SD = 0.343, Δk = 399.17, PCA results show three distinct groups with little overlap: (1) Gooseberry and Smooth Knolls, (2) Dalley Farm and Panguitch Fly Shop, and (3) Cedar City and Kanarraville form Fig.  which suN = 5 runs per k; Figs k = 4 (LnP(D) = −1927.714, Δk = 6.91) in which three genotype clusters are identified for the West Desert Colonies and all individuals were admixed between two of the three genotype clusters. Individuals from the Dalley Farm and Panguitch Fly Shop colonies assign primarily to one of the three clusters present in West Desert, but have some admixture with the genotype cluster that East Creek, Smooth Knolls and Gooseberry assigned to. BAPs identified eight genotype clusters, with Dalley Farm, Panguitch Fly Shop, East Creek, Smooth Knolls, and Gooseberry assigning to distinct clusters. Unlike with the native colonies there was substantial overlap in PCA space among the colonies in the Pausaugunt and Awapa Recovery Units. However, changes in log of assignment if groups are moved to a different cluster show a clearer pattern of separation among the colonies  = −2470.73, SD = 0.485, Δk = 1019.53, FST values were quite high, there were no significant pairwise FST's among colonies when adults were analyzed separately, but sample sizes were quite small  and for native and transplanted colonies combined . All recovery units were also significantly differentiated from each other .Although pairwise ed Table . Nm esties Table . Smooth kerham's  θ calculF = 1.701, P = 0.203; Fig. F = 45.358, P = 0.000; Fig. We did not observe an isolation‐by‐distance pattern for all pairwise colony comparisons within and among recovery areas . Effective population sizes were exceedingly small for all colonies sampled ranging from 1.9 (PF) to 13.9 (SN) per colony , suggesting small founder populations and/or extensive losses of genetic variation through random genetic drift when populations were small. Ne was also small for the genotype clusters identified among the native colonies by STRUCTURE .All populations showed evidence of genetic bottlenecks under both the SMM and TPM mutation models . Overall, the allelic diversity at these microsatellite markers in Utah prairie dog was lower than the species the microsatellites were developed from  but not substantially so. In contrast, the black‐tailed prairie dog has maintained genetic variation despite extensive habitat fragmentation , Idaho ground squirrel , Mohave ground squirrel , and Perote ground squirrel , reveals that the Utah prairie dog is among the most genetically depauperate , allelic richness ranged from 2.1 to 3.51 (based upon a sample size of six) and expected heterozygosity per population ranged from 0.393 to 0.658. Despite the vulnerable or endangered status of these species, they are harboring considerably more genetic variation than the Utah prairie dog.The Utah prairie dog together with the Mexican prairie dog remains listed as endangered on the IUCN Red List. Comparison of levels of genetic variation found in the Utah prairie dog with the data available for other ground‐dwelling sciurids, which have IUCN vulnerable or endangered status, including the European ground squirrel  that loses genetic variation due to random genetic drift at the same rate as observed in the real population Wright , 1940. TThe ESU concept has been widely embraced by the conservation biology community Moritz . EvolutiOur Bayesian analysis of the native colonies support 3–5 genotype clusters depending upon the clustering algorithm used  we report here or Meirmans and Hedrick's  for Utah prairie dogs. The high and significant FST values we observed may be the result of historical genetic structure, genetic bottlenecks, and the recent effects of random genetic drift at small population sizes. The pattern of isolation‐by‐distance among recovery units further suggests low rates of contemporary gene flow between these areas.The pairwise h et al.  reportededrick's  correcteThe presence of unique and rare alleles also supports genetic differentiation and colony isolation. The Smooth Knolls colony, which is quite isolated from the other colonies sampled, has two unique alleles and the highest number of rare alleles despite a very small census size. The transplanted populations maintain similar levels of heterozygosity compared to the native colonies and also contain unique and rare alleles. Together these data paint a picture of three genetically distinct groups comprised of colonies that are now largely isolated.Humans have decimated Utah prairie dog populations through direct elimination campaigns and habitat destruction/fragmentation/conversion. The remaining colonies have extremely low levels of genetic variation and very small effective population sizes. The human population in southern Utah is growing and the Utah prairie dog habitat will continue to face increasing development pressure which could lead to additional losses of genetic diversity. For a species that is already genetically compromised, this would be disastrous.Wal et al.  recentlyDue to the low overall genetic diversity within the Utah prairie dog species as a whole, human‐mediated translocations among recovery units is not likely to increase diversity. At a minimum there are three distinct genotype clusters among the native colonies representing the repository of extant variation of the species. Our analyses suggest three management actions that might improve gene flow and maximize maintenance of remaining genetic diversity in Utah prairie dogs within and among the recovery units: (1) the protection and maintenance of suitable habitat between existing colonies which could provide critical corridors for dispersal and subsequent gene flow. The small population sizes of most of the colonies sampled for this study suggests that maintenance of unique and rare alleles as well as overall genetic diversity can only be achieved through increases in population size and dispersal among neighboring populations within recovery units. We emphasize that populations in the Pausaugunt recovery unit, although biogeographically distinct, are not a genetic entity. Landscape genetic analyses of the black‐tailed prairie dog show that introduction of plague and habitat fragmentation over the 20th century has resulted in semi‐isolated populations that now function as metapopulations , but the prairie dog populations appear to be stable (adult spring count; USFWS, None declared.


Genetics is the study of heredity, which means the study of genes and factors related to all aspects of genes. The scientific history of genetics began with the works of Gregor Mendel in the mid-19th century. Prior to Mendel, genetics was primarily theoretical whilst, after Mendel, the science of genetics was broadened to include experimental genetics. Developments in all fields of genetics and genetic technology in the first half of the 20th century provided a basis for the later developments. In the second half of the 20th century, the molecular background of genetics has become more understandable. Rapid technological advancements, followed by the completion of Human Genome Project, have contributed a great deal to the knowledge of genetic factors and their impact on human life and diseases. Currently, more than 1800 disease genes have been identified, more than 2000 genetic tests have become available, and in conjunction with this at least 350 biotechnology-based products have been released onto the market. Novel technologies, particularly next generation sequencing, have dramatically accelerated the pace of biological research, while at the same time increasing expectations. In this paper, a brief summary of genetic history with short explanations of most popular genetic techniques is given. Due to rapid advances in genomic technologies, genetics analyses have become essential in clinical practice and research. During the past decade, a great stride has been made to unravel underlying mechanisms of genetic-related disorders. Landmarks in genetic history are summarized in  On the Origin of Species by means of Natural Selection in 1859, Gregor Mendel introduced the fundamental laws of inheritance in 1865. This was crucial for understanding that “some characteristics of the organisms are inherited through genes.” Mendel's rules were improved by the experiments of Thomas Hunt Morgan in 1910 who discovered that genes were responsible for the appearance of a specific phenotype located on chromosomes. In 1911, the first genetic map was achieved by mapping the fruit fly genes. From the 1800s until the middle of the 1900s, it was not understood that the structure of hereditary genetic material was responsible for the inheritance of traits from one generation to the next. In 1953, Watson and Crick described the double-stranded, helical, complementary, and antiparallel model for DNA [Looking at the history in brief, genetics is the term introduced for the study of genes in organisms. Many early discoveries contributed as important milestones to evolve the study of genomes as it is applied today. One of the crucial steps that enabled visualizing intracellular structures was the invention of the single-lens optical microscope by Janssen in 1595 . A Swiss for DNA . They shThe first genetic analysis was performed in the field of cytogenetics. Although it was published that normal human chromosome number was 48, Tjio and Levan reported in 1956 that the correct number was 46 –9. AfterDespite the establishment of high-resolution techniques which enabled revealing many known or unknown genetic syndromes, several cases having submicroscopic aberrations that were not visible at resolution between 500 and 1000 bands remained undiagnosed. A new technique called fluorescence in situ hybridization (FISH) was developed in the field of molecular cytogenetics in 1982 . In thisBeing time-consuming and expensive to evaluate chromosomal rearrangements in the whole genome by FISH led to the development of new techniques such as array-based comparative genomic hybridization –35. CompArray-CGH failed to detect the recessive disease genes, mosaic aneuploidy, uniparental disomy (UPD), or heterochromatic rearrangements. Because of this disadvantage, it is thought to combine with SNP arrays to improve the resolution of array-CGH . These aLarger genomic changes such as deletions, duplications, and translocations can be detected by conventional karyotyping, FISH, or array-CGH methods but single nucleotide changes cannot be detected by these techniques. Molecular genetic techniques were rapidly developed after the establishment of polymerase chain reactions that enabled generating thousands to millions of copies of a particular DNA sequence . Mullis Taq DNA polymerase that was selected the first “Molecule of the Year” by Journal of Science was a major advantage in PCR technology . AutomatWith the advances in the field of molecular genetics, it became possible to launch the Human Genome Project to reveal the complete human genome. The programme was launched in the USA with an effort of the Department of Energy and the National Institutes of Health in collaboration involving 20 groups in 1990. The first draft of human genome was published in 2001 by The International Human Genome Sequencing Consortium . This fiIn addition to cost-effective advantages, sequencing the small part of the genome allows reducing the number of variations that in turn reduce the cost and time needed for data interpretation . Targete BCR/ABL  through the improvements of the molecular techniques [Approximately 10 years ago, karyotyping was the gold standard in patients with intellectual disability but array-CGH analysis has become the first line diagnostic test replacing karyotyping and FISH nowadays. As evident from this example, approaches to the genetic-related diseases could change in parallel with the advances in technology and science. “Philadelphia chromosome” is one of the oldest evolutionary examples of personalized medicine by revealing the etiological factor and the treatment options of a disease step by step by using the genetic analysis as the improvements in the genetic techniques were established. In 1960, a small chromosome called Philadelphia chromosome was identified to be the cause of the chronic myeloid leukaemia (CML). It was shown in 1973 by the chromosome banding technique that this chromosome was a result of a translocation between chromosomes 9 and 22 , 55. It chniques . The folchniques .Genetic test that will be used in the diagnosis should be chosen very carefully, which might not be the newest or the most sophisticated one. Sometimes only a karyotype could be enough to identify the genetic condition in the patient instead of more complicated array-CGH or NGS methods. As the technology in genetics rapidly evolves, new insights in terms of data interpretation and genetic counseling including pretest counseling, return of results, and posttest counseling need to be considered. Databases and consortium reports regarding the experiences of the clinicians and geneticists are crucial for integration of genomics into clinical practice.If the developments in genetics and computer technologies continue to progress at their current speed, history has shown us we can look forward to some amazing developments in human life in the very near future. Some realistic scenarios of human life in the future could even see us carrying identity cards, which include our genome characteristics, rather than the format we are currently using. Gene corrections, cloned individuals and organs, and even genetic-based techniques as a primary laboratory analysis in almost all human diseases for a clinician will no longer be a dream. We have come to the point nowadays where genetic testing is commercially available; the individual now has the possible means to access this delicate information named as direct to consumer (DTC) genetic testing. Contrary to the traditional hospital or physician based testing, accessing an individual's genetic information without medical or specialized interpretation has gradually been finding a place in our daily lives. Today, more than 25 companies, from all over the world, offer DTC service to the public. Serious concerns, however, regarding the use of this kind of service, have been raised in terms of misleading and incidental results derived from unproven or invalidated data. Moreover, there is also a significant risk for unauthorized use of sensitive genetic information by big business, particularly in the fields such as health insurance. On the other hand, DTC does provide early awareness of genetic diseases and thereby offers individuals the opportunity to play an active role in their own health care. The issue at stake here leads us to the same difficult medical ethics dilemma: patient autonomy and right to know one's genetic composition versus nonmaleficence.To conclude, in parallel with the rapid developments in the field of genetic technologies, ethical and legal issues regarding the implementation of those technologies need to be addressed. Because use of personal genetic information looks certain to directly impact our daily lives in the near future, protocols need to be discussed in detail, with guidelines provided and updated regularly as part of a regulated multidisciplinary approach.


Amphicarpaea bracteata is unusual in producing aerial and subterranean cleistogamous flowers that always self‐fertilize and, less commonly, aerial chasmogamous flowers that outcross. Although both morphologic and genetic variants are known in this highly selfing species, debate continues over whether this variation is continuous, reflecting the segregation of standing genetic variation, or discontinuous, reflecting distinct taxa that rarely intercross. We characterized SNP variation in 128 individuals in southern Wisconsin to assess within‐ and among‐population variation at 3928 SNPs. We also assessed genotype and leaf morphology in an additional 76 individuals to connect phenotypic variation with genetic variation. Genetic variation maps onto three strongly divergent and highly inbred genetic groups showing little relation to site location. Each group has a distinct phenotype, but the divergence of these groups differs from the varietal divisions previously identified based on morphological characters. Like previous authors, we argue that the taxonomy of this species should be revised. Despite extensive sympatry, estimates of among‐group migration rates are low, and hybrid individuals were at low frequency (<2%) in our dataset. Restricted gene flow likely results from high selfing rates and partial reproductive incompatibility as evidenced by the U‐shaped distribution of pairwise FST values reflecting “islands” of genomic divergence. These islands may be associated with hybrid incompatibility loci that arose in allopatry. The coexistence of lineages within sites may reflect density‐dependent attack by species‐specific strains of pathogenic fungi and/or root‐nodulating bacteria specializing on distinct genotypes.The amphicarpic annual legume  The rapid development of accessible molecular genotyping and sequencing methods has greatly improved our ability to catalog biodiversity  fell into lineage Ia, the treatment of var. bracteata was less clear, as plants in both of the remaining lineages Ib and II were sparsely pubescent yet strongly differentiated in other features , and a shade‐native ecotype with narrow leaflets (consistent with Parker's lineage II)  examine differences among the three lineages at many more loci than previously studied, (2) use such data to assess the extent of gene flow and potential reproductive isolation between lineages, and (3) assess correlations between genetic and phenotypic data to clarify the nature of the variants and the extent to which morphology supports the recognition of cryptic species within the Amphicarpaea bracteata complex.In short, there is strong evidence that Amphicarpaea bracteata (Fabaceae) is an annual trailing herb, 1–5 ft long, common to moist woodland habitats of the eastern United States and southeastern Canada  for phenotyping and high resolution melt (HRM) genotyping. We chose these sites based on results from the GBS analysis, to ensure that plants from all three lineages were included in this dataset (Table S1). Upon collection, plants were placed immediately in sealed plastic bags and kept cool for transport back to the lab. We scanned each leaf using a Canon Canoscan LiDE 50 flatbed scanner and then preserved leaves in a plant press on the day they were collected. These specimens were deposited at the Wisconsin State Herbarium (WIS). We preserved additional leaf tissue from all plants on silica gel for genetic analysis.We revisited three sites in August 2015 to sample an additional 79 plants  was set to 5 and the distance between catalog loci (cstacks parameter n) was set to 3. After assembly, loci and individuals were filtered using the Stacks populations program, vcftools  is in the family of reduced‐representation techniques for high‐throughput sequencing . Twenty replicates were run with 4 chains each using a static heating scheme , burn‐in of 10,000 steps, and 10,000 recorded steps per chain with a sampling increment of 500. MIGRATE estimates mutation‐scaled population size, θ = 4Neμ, and mutation‐scaled migration rate, M = m/μ. We then calculated the number of migrants per generation as Nem = (1/4)*θ*M. The variance of these estimates depends on the number of unlinked loci . Nevertheless, the very large number of SNP loci compensate in part for this, reducing the variance associated with these estimates to reasonably small values.We used MIGRATE v.4.2 to estimate historical effective population sizes and migration rates among lineages using the coalescent (Beerli and Felsenstein i Beerli . BecauseHigh resolution melt (HRM) genotyping uses real‐time PCR to identify variants based on small differences in the melting curves of amplicons  at the same time to use as HRM reference samples. Real‐time PCR for HRM genotyping of small amplicons was performed at the UCLA Genotyping and Sequencing Core facility using a LightCycler 480 Real Time PCR System  in 10 μl reaction volumes with the LightCycler 480 High Resolution Melting Master kit (Roche). We analyzed melting curves and called peaks for each sample using the LightCycler 480 software release 1.5.1.62, confirming with visual inspection.2 section on the abaxial surface of the terminal leaflet; and the ratio of the lengths of the terminal to the right lateral petiolule (pet_dim). Leaf hairs were counted using photographs taken with a Firefly GT200 handheld digital microscope.We analyzed variation in leaf morphology from the scanned images using a two‐tiered approach to determine whether we could distinguish the three genotypic lineages based only on their leaflet structure. To compare samples, we first compiled measurements from the scanned leaf images for the samples subjected to HRM genotyping using ImageJ , we did not include terminal leaflet shape PC in this analysis. We used leave‐one‐out cross‐validation to determine the extent to which genotype can be predicted based on leaf characters.To compare phenotypic differences among lineage groups, we first conducted one‐way ANOVAs on leaf measurements  to determine which traits varied significantly among lineages. We also analyzed these variables, together with the first principal component from the elliptic Fourier analyses on the lateral leaflet shape, using linear discriminant analysis (LDA). Because the first principal component of terminal leaflet shape and term_dim were highly correlated .In total, we obtained 313,998,762 demultiplexed reads for 141 n = 5) from the other individuals. Axis 2 (18.3% of the variation) divides the remaining individuals into two additional lineages . Two individuals intermediate between Groups 2 and 3 appear to be putative hybrids. Groups were spread across multiple sites, with most sites hosting more than one group (Table S1). Individuals from putative parental lineages always occurred at sites where a hybrid was found.It is clear from the PCA that site locations do not dominate the variation in the genetic data Fig. . InsteadDN = 0.65). Group 2 and Group 3 are much more similar (DN = 0.22).Summary statistics calculated for these groups further support the contention that these represent divergent, highly homozygous lineages Table a. Genic FIS varying from a low value of 0.65 at site GT to >0.90 at most other sites. FST among sites within Group 2 is 0.10.We additionally evaluated population‐level processes within the largest group  which was also the only group found at all seven sites Table b. HeteroHo values at least ten times higher than the averages observed within Groups 2 and 3  ranging from 0.00183 to 0.00317. These values are similar to those estimated for the closely related cleistogamous soybean Glycine max  are low and asymmetric for Group 1, with immigration from Groups 2 and 3 only half the values of emigration (0.2 vs. 0.4). Groups 2 and 3 have symmetrical migration rates of approximately 0.4  than the Group 2 vs. Group 3 comparison . Three individuals, all collected from site MSF, had HRM alleles specific to both Group 1 and Group 3 and were discarded from further analysis.P < 0.001) for all characters , Group 2 matches var. comosa (Parker's lineage Ia), and Group 3 matches the wide‐leaved ecotype of var. bracteata (Parker's lineage Ib).Our results are concordant with the phenotypes reported for the three lineages identified by Parker , and ourAmphicarpaea bracteata has been described both as a single, highly variable taxon . We also see that taxonomic subdivisions of A. bracteata are not concordant with relationships among the genetic lineages.A. bracteata matches previous work based on 18 allozyme loci  place the lineage corresponding to our Group 1 as basal to the other two A. bracteata lineages  rather than leaf pubescence.Our combined genetic and phenotypic data suggest that a taxonomic revision of A. bracteata in sympatry: (1) limited outcrossing due to the high selfing rate; (2) assortative mating during outcross events, perhaps due to differences in flower color among lineages; and (3) postmating barriers that reduce the fitness of hybrid individuals. The mating system of amphicarpic plants certainly limits outcrossing events, as evidenced by the high homozygosity and inbreeding coefficients documented here and previously  are specialists that only associate with distinct Bradyrhizobium genotypes. The other lineage  is a symbiont generalist, an apparently derived character that could increase plant fitness and promote competitive exclusion in some situations .Table S1. Sample sizes for each site. Sample sizes for each lineage  within sites are given in parentheses.Table S2. Mutation‐scaled migration rate, M (= m/μ), with 95% confidence intervals for each Amphicarpatea bracteata genetic group.Table S3. High resolution melt (HRM) primers and alleles used to assign samples to genetic groups.Table S4. Results of leave‐one‐out cross‐validation analysis predicting lineage membership.Click here for additional data file.


Eudyptula, the world's smallest penguin. Specifically, we use a suite of genetic markers to reveal that two congeneric taxa  co-occur in southern New Zealand, with only low levels of hybridization. Coalescent modelling suggests that the Australian little penguin only recently expanded into southern New Zealand. Analyses conducted under time-dependent molecular evolutionary rates lend support to the hypothesis of recent anthropogenic turnover, consistent with shifts detected in several other New Zealand coastal vertebrate taxa. This apparent turnover event highlights the dynamic nature of the region’s coastal ecosystem.Molecular genetic analyses present powerful tools for elucidating demographic and biogeographic histories of taxa. Here we present genetic evidence showing a dynamic history for two cryptic lineages within  Molecular and computational analytical techniques provide important tools for assessing biological history , 2, inclMytilus trossulus, was masked by the invasion of the Mediterranean blue mussel, M. galloprovincialis [Human activity is frequently implicated as a cause of species decline and extinction, but can also facilitate major range shifts in some taxa , 11–13. Eudyptula minor , endemic to southern Australia and New Zealand (NZ), is the world's smallest extant penguin species [E. minor vocalisations were also differentiated between Australia and NZ, with Otago birds exhibiting calls similar to those of Australian birds [Eudyptula comprises multiple taxa remains unresolved.The little penguin,  species . Systema species , early m species . In contForster, 81, endem species . ComponeForster, 81, endemForster, 81, endeman birds  suggestean birds , and thuE. minor relates to the mechanism whereby these two lineages—potentially distinct species—have come to co-occur in NZ. Recent studies of other vertebrate taxa have revealed several cases of trans-oceanic self-introduction following human impacts [An additional question concerning  impacts . The mtD impacts , 18 appr impacts , 13. Und impacts .Eudyptula comprises two distinct taxa that co-occur in NZ; and (2) that the Australian lineage in Otago represents a recent invasion. We use Markov chain Monte Carlo coalescent analysis to assess timeframes of population divergence.In this study we use a suite of nuclear DNA markers (microsatellites and an intron marker) to test the following hypotheses: (1) that E. minor were collected from localities spanning the distributional range of this species  using universal primers FIB-BI7U and FIB-BI7L [2, 200 μM of each dNTP, 0.25 μM of each primer and 0.5 units of Taq DNA polymerase . Cycling parameters consisted of an initial denaturation at 95°C for 5 min, followed by 38 cycles at 95°C for 20 s, 61°C for 25 s and 72°C for 90 s, with a final extension of 72°C for 10 min. Gel purification of PCR products was necessary due to double bands. Bands of approximately 1100 bp were cut from the gel and purified using the Illustra GFX PCR DNA and Gel Band Purification Kit . PCR fragments were sequenced in both directions, and the alignment was trimmed to 1009 bp. Haplotypes of heterozygous individuals were resolved probabilistically using PHASE v. 2.1 with a phase-probability threshold of 0.95, implemented in DNASP v. 5.10.1 [The seventh intron of the nuclear β-fibrinogen gene (β-fibint7) was amplified for a spatially representative subset of FIB-BI7L . β-fibin. 5.10.1  in SPLIT. 5.10.1 . All seqK) of individuals. For the complete dataset containing 477 individuals from all sampling locations and 19 microsatellite loci  we performation , 42. 95%ormation , as implormation . CLUMPP ormation  was usedormation .Levels of genetic variability for microsatellites and mtDNA were assessed by calculating average number of alleles, expected heterozygosity, observed heterozygosity, numbers of haplotypes, and haplotype and nucleotide diversity in ARLEQUIN. Allelic richness corrected for sample size differences was computed using ADZE v. 1.0 .http://popart.otago.ac.nz).We quantified levels of genetic differentiation between populations by calculating pairwise Fst and Φst values in ARLEQUIN. Φst values for mtDNA were calculated using Kimura-2-Parameter genetic distances. Significance of Fst and Φst values between populations was tested by permuting haplotypes or alleles between populations . P-values were adjusted for multiple comparisons. We further tested for hierarchical differentiation within and between the NZ vs. AUS lineages using Analysis of Molecular Variance (AMOVA)  performeSeparate analyses on NZ and AUS lineage subsets of the dataset, including Bayesian clustering, AMOVA and Mantel test are described in Eudyptula lineages. First, the assignment method in STRUCTURE was used with 500,000 burn-in, 1,000,000 steps with two groups (AUS and NZ) and migration prior ayText>[We employed two different methods to detect hybrid individuals and evaluate levels of gene flow between r ayText>1. Other r ayText> was run The age of divergence between Otago and Phillip Island populations was assessed under the “Isolation with Migration” framework , employi-6 mutations site-1 year-1 [-6 mutations site-1 year-1) derived from Adélie penguin family comparisons [-6 mutations site-1 year-1) to explore demographic history. Adélie penguin rates were based on the mtDNA control region. The slower rate estimate was derived from comparisons of cytochrome b (cyt b) and control region (CR) divergence between the AUS and NZ lineages  derivedparisons  and a slectively ). A diveively [b ; given tθ (= 4Neμ) were set at 20, and the upper limit of the uniform population divergence time prior was set to 1.0. Exponential priors for gene flow were set around a value approximating a mean of 6x10-6. Analyses were also carried out under a model assuming no post-divergence gene flow.We used uniform priors for population size and divergence time parameters, and exponential priors for gene flow, given an expectation that low rates of gene flow were likely. Upper limits on uniform priors of An initial run was conducted until stationarity was achieved, assessed based on the lack of trends in posterior parameter estimates, employing MCMC sampling with 80 chains, a geometric chain heating scheme with first and second heating parameters of 0.95 and 0.50, respectively, and eight chain-swap attempts per step. This was then used to seed 24 independent (different random number seed) 24-hour runs each with a short (4 hour) burn-in, but otherwise using the same parameters as above. These 24 runs produced a total of 39,308 (migration) or 38,960 (no migration) genealogies for estimation of model parameters.Following FDR correction there was evidence for linkage between some loci, however, the signal was inconsistent between populations and all loci were retained for further analyses. Only one locus (Em15) deviated consistently from HWE after FDR correction and was removed from subsequent analyses  and New Zealand (NZ) mtDNA-defined lineages  and Φst value of 0.855 (p < 0.0001) for microsatellites and mtDNA control region, respectively. Within the NZ and AUS lineages, many population comparisons yielded significant pairwise Fst and Φst values, and the Chatham Island population was particularly strongly differentiated from all other NZ lineage populations , likely sourced from the Otago population . While tDivergence-time estimates for the Otago and Phillip Island populations consistently support a recent (Holocene) isolation event , and faiEudyptula penguins confirm that the genus comprises two genetically distinct units. These units broadly correspond to the geographic regions of Australia and NZ, with the exception that the Australian lineage is also present in southern NZ’s Otago region. Multilocus coalescent analyses imply that the Otago population established more recently than previously suggested.Our multilocus genetic analyses of Eudyptula microsatellite markers (19 loci) revealed a clear distinction between NZ and AUS lineages, and thus provide broad genomic support for the previously reported mtDNA-based distinction [Spheniscus penguins . Additionally, Tavares & Baker [Eudyptula species.Analyses of tinction , 18. The markers  loci rev & Baker , furtherEudyptula lineages typically involved hybrid individuals  and thus are most likely attributable to introgression.The β-fibint7 locus revealed less differentiation between the lineages, with some alleles shared between NZ and AUS lineage individuals. While such patterns could reflect either ancestral polymorphism or incomplete lineage sorting , 58, theEudyptula penguins in NZ have not experienced terrestrial vertebrate predators until recently, whereas Australian birds might have regularly encountered carnivorous marsupials [In addition to genetic data, there is clear biological evidence supporting a species-level distinction. Feather-colour exhibits significant differentiation between lineages for their blue chroma and maximum brightness . Moreoversupials . Anotherrsupials . Althougrsupials , 66, it rsupials .Eudyptula novaehollandiae [Eudyptula minor [Based on our multilocus genetic analyses and concordant biological evidence, we recommend the Australian little penguin to be elevated to full species status, llandiae , with itllandiae . The NZ la minor  with theGiven controversies around the time-dependency of molecular rates (TDMR) , 53, 71,Eudyptula population declines apparently occurring soon after human settlement. Specifically, while Eudyptula is one of the most widely-represented taxa in many of NZ’s pre-human deposits and early archaeological middens, the genus is apparently absent from the majority of late prehistoric midden sites [Eudyptula colonised Otago before human settlement in NZ. However, given archaeological evidence a post-human arrival for this lineage seems likely. Comprehensive aDNA analyses of fossil and archaeological Eudyptula remains similarly support recent (post-human) turn-over of Eudyptula lineages in southern NZ (Grosser unpublished data).In addition to coalescent analyses (above), archaeological records provide further evidence of anthropogenic impacts, with substantial en sites . Based oGenetic exchange between the Australian and NZ little penguins was restricted to the New Zealand mainland where they co-occur in secondary-contact. It is, however, not yet clear whether introgression of the AUS DNA into NZ populations is exclusively caused by Otago individuals, or if Australian birds occasionally breed in NZ. While the frequency of trans-Tasman dispersal is unknown, it seems reasonable to assume that such events are rare, given that these landmasses are separated by approximately 2,000 km of ocean. Nevertheless, our data demonstrate eastward trans-Tasman migration in the recent past, consistent with prevailing winds and ocean currents e.g., , 74. It We observed a higher degree of introgression from the NZ species into Otago, matching the theory that a species expanding into the range of a sister taxon will experience greater introgression than the resident species . NeverthEudyptula conservation status. While little penguins are globally evaluated as ‘least concern’, their general demographic trend is one of decline [Elevation of the Australian little penguin to full species status warrants the reassessment of  decline . In NZ,  decline , with su decline , 79. Cur decline .Our study's findings represent the second recognition of new extant penguin species diversity within a decade , and exeS1 AppendixSeparate analyses on NZ and AUS lineage subsets of the dataset.(DOCX)Click here for additional data file.S2 AppendixProvided as an Excel file in GenAlEx format.(XLS)Click here for additional data file.S1 FigK for the complete dataset according to the Evanno method.Selection of optimal number of clusters (TIFF)Click here for additional data file.S2 FigK = 2 to K = 5. Individuals are represented by vertical bars and colour indicates proportional membership of the individual to a genetic cluster. Black lines separate sampling localities as named below the plot.Based on STRUCTURE analysis of the complete dataset for (TIFF)Click here for additional data file.S3 Figq1 and q2; the top plot represents the upper PI of q1 and the lower PI of q2; and the bottom plot represents the lower PI of q1 and the upper PI of q2.The middle plot represents the mean values of (TIFF)Click here for additional data file.S1 Table1samples newly acquired for this study (collected by researcher in connection with other studies); 2samples newly acquired for this study; 3samples present at the Department of Zoology from previous studies. DoC–New Zealand Department of Conservation.Information on sampling location, sample provider, collection date and tissue type of samples used for population genetic analyses. (DOCX)Click here for additional data file.S2 TableE. minor groupings based on genotypes from 19 microsatellite loci together with sequences from mtDNA control region. NZ–New Zealand, AUS–Australia. Values that were significantly different from zero are indicated by an asterisk.Assessment of hierarchical genetic variation between regional (DOCX)Click here for additional data file.


Oryza sativa L.) are direct seeded rices grown on hill slopes of different gradients. These landraces have evolved under rainfed and harsh environmental conditions and may possess genes governing adaptation traits such as tolerance to cold and moisture stress. In this study, 64 hill rice landraces were collected from the state of Arunachal Pradesh of North-Eastern region of India, and assessed by agro-morphological variability and microsatellite markers polymorphism. Our aim was to use phenotypic and genetic diversity data to understand the basis of farmers’ classification of hill rice landraces into two groups: umte and tening. Another goal was to understand the genetic differentiation of hill rices into Indica or japonica subspecies.Hill rices  and tening . We did not find significant difference in days to 50 % flowering between the groups. Principal component analysis revealed that two groups can be distinguished on the basis of kernel length-to-width ration (KLW), kernel length (KL), grain length (GrL), grain length-to-width ration (GrLW) and plant height (Ht). Stepwise canonical discriminant analysis identified KL and Ht as the main discriminatory characters between the cultivar groups. Genetic diversity analysis with 35 SSR markers revealed considerable genetic diversity in the hill rice germplasm . Pair-wise allelic difference between umte and tening groups was not statistically significant. The model-based population structure analysis showed that the hill rices were clustered into two broad groups corresponding to Indica and Japonica. The geographic distribution and cultivars grouping of hill rices were not congruent in genetic clusters. Both distance- and model-based approaches indicated that the hill rices were predominantly japonica or admixture among the groups within the subspecies. These findings were further supported by combined analysis hill rices with 150 reference rice accessions representing major genetic groups of rice.According to farmers’ classification, hill rices were categorized into two groups: japonica or admixture among the subpopulations of Indica or Japonica. The findings are useful for utilization and conservation of hill rice germplasm.This study collected a valuable set of hill rice germplasm for rice breeding and for evolutionary studies. It also generated a new set of information on genetic and phenotypic diversity of hill rice landraces in North-Eastern region of India. The collected hill rices were mostly The online version of this article (doi:10.1186/s12863-016-0414-1) contains supplementary material, which is available to authorized users. Oryza sativa L.) is one of the important crops in the world. Being a model organism with fully sequenced genome, it also affords unique opportunities to use genomic approaches to study its domestication, adaptive selection, and the history of crop improvement [Indica and Japonica, three to seven genetically distinct groups have been identified within global rice (Oryza sativa) germplasm sets in different studies [O. sativa, resulting in >120,000 distinct rice varieties [Rice is the primary food source for more than half of the world’s population . Over 90rovement , 3. The rovement –6). In a studies –14. Nume studies –22. Such studies , and for studies . The cularieties . An assejhum) and sedentary agriculture. Shifting or ‘slash-and-burn’ cultivation is the earliest form of agriculture and is still practiced in vast areas of the state. About 76 % of the total cropped area in the state is under jhum cultivation.The North-Eastern (NE) region of India, due to its unique eco-geographical features and high ethnic diversity, possesses at least 10,000 indigenous rice landraces which cultivated under upland, lowland and deep water conditions . The impjhum fields), plateaus, terraces and river beds. A wide range of rice landraces were found throughout the state. Sometimes it depends on the tribal communities who inhabit the area. It was estimated that more than 70 % of the total rice varieties grown in the state are traditional cultivars or landraces having low to very low productivity [jhum cultivation system possess many adaptive traits such as cold tolerance important for crop improvement programmes. Cold-tolerance in hill rice landraces was also observed in high altitude (1300–2200 m) rice areas in Nepal [jhum) rice cultivars of Arunachal Pradesh.Rice is the principal crop of Arunachal Pradesh and it is grown in 44.7 % of the total cropped land and accounts for 70.3 % of the total food grain production . Rice pructivity . Despitein Nepal . Similarviz, East Kameng, Papum Pare and Kurung Kumey of the state of Arunachal Pradesh was conducted for the collection of hill rice landraces. These rices are direct seeded, grown on upland fields, usually on sloping hill sides (jhum lands), and are grown as rainfed during June to September. During the collection trip, we interviewed local farmers to gather information on significance of naming a landrace, its cultural value and popularity, and production practices of local farmers. The indigenous farmers of the surveyed region rely on gathering forest products, hunting and cultivation of rice and maize for their subsistence. In the present study, we phenotyped these rice landraces for 16 agro-morphological and grain characteristics, and genotyped them with 35 SSR markers. The specific objectives of this study were to: (i) collect information on the meanings of the variety names, special uses or properties, and important agronomic characteristics; (ii) study the agro-morphological variability; and (iii) understand the genetic relatedness and structure of these landraces.In 2012, an exploration trip to three districts A total of 67 hill rice accessions were collected from 32 villages in three districts  of Arunachal Pradesh, India during a collection trip from November 2–15, 2012 , two aus , three Basmati , three short-grain traditional aromatic  and a single accession each of tropical japonica (‘Azucena’) and japonica admixture (‘Dular’). Pure seeds of these accessions were obtained from ICAR-National Rice Research Institute, Cuttack, India. These varieties were used to understand genetic grouping of the hill rice accessions, and also to act as a molecular weight reference in DNA gel electrophoresis. We did not include these varieties in phenotypic evaluation as the plant growth was very poor for most of the accessions.A total of 15 control varieties were selected for SSR genotyping along with the hill rices . We sampled 150 accessions from the originally reported 234 accessions used in Garris et al. [To provide a reference for the rice subpopulation classification in the current study, we also used the SSR fingerprinting data of 150 rice accessions (here we denoted these as reference accessions) previously reported in the genetic diversity study by Garris et al. . The bans et al.  based ons et al. .Kharif season (June-November) under rainfed upland conditions. The soil of the field is an acid alfisol with a pH of 5.3, organic C 1.13 % and available N 211 kg/ha. Farmyard manure (10 tonnes/ha) was incorporated into the soil during land preparation. No chemical fertilizers and pesticides were used during crop growth period. A manual weeding was conducted to keep the crop weed free. The accessions were line-sown in 1 m x 1.5 m plots (4 lines/accession) using an augmented block design during first week of June. A spacing of ~0.25 m between the plants and 0.45 m between the rows was maintained. Phenotypic data, listed in Table Sixty four hill rice accessions and three check varieties  in 2015 http://www.gramene.org/markers/microsat/). Information about these markers is given in Additional file Thirty five SSR markers were designed from the ‘Gramene’ marker database  was performed on the correlation matrix of the data to understand the most important variables contributing to the total phenotypic variation among the accessions. PCA represents the simplest and most commonly used multivariate method to visualize the grouping of accessions based on component loadings. Ward’s hierarchical clustering was used to understand the relationships among rice accessions based on phenotypic data. All these analyses were performed using IBM-SPSS Statistics version 20.0 [Summary statistics such as mean, standard deviation (SD), minimum and maximum values, and coefficient of variation (CV) were determined. The mean data were standardized by deriving ion 20.0 .K) evaluated here ranged from 1 to 8. The analysis was performed using five replicate runs per K value, a burn-in period length of 5000, a run length of 50,000, and a model allowing for admixture and correlated allele frequency. ‘Structure harvester’ programme (http://taylor0.biology.ucla.edu) was used to determine the final K value(s) based on both the LnP(D) and Evanno’s ΔK [K = 2–4 were then performed with a burn-in period of 10,000 and a run length of 100,000. The membership coefficient from the run with the lowest likelihood value was used to assign each accession to the K = 1 to 4 subpopulations based on the estimated membership coefficients.Population structure of 64 hill and 15 control rice accessions was examined using the Bayesian model-based approach implemented in STRUCTURE V2.3.4 . The numnno’s ΔK . SubsequHe), heterozygosity (Ho) and polymorphism information content (PIC) were calculated using PowerMarker V3.25 [Rs) and Wright’s fixation index (Fst) values were calculated using FSTAT V2.9.3.2 [The average number of alleles per locus (AN), major allele frequency (MAF), gene diversity . The reference set also included some ‘admixture’ accessions. For clustering, a pair-wise genetic distance matrix was calculated in PowerMarker following C. S. Chord distance method [Fst and allelic differences (FPTest) between the groups were calculated as stated earlier.Cluster analysis was conducted on hill and reference accessions to understand the grouping of hill rices in respect to different genetically defined groups , large grained-late maturing rice, and (ii) tening, small grained-early maturing types  umte and tening groups of hill rice are given in Table tening group showed higher average value of DtF (120.8 d) than umte (115.8 d). However, the difference was prominent for grain and kernel characteristics. The umte accessions had longer grains with an average value of 6.9 mm than that of tening (6.2 mm). Similarly, the value of KL in umte (5.4 mm) was higher than that recorded in tening (4.6 mm). Both the highest values for GrLW and KLW were recorded in umte. On average, the plants of umte accessions (81.1 cm) were taller than the tenings (69.9 cm). The tenning accessions produced larger leaves (59.7 cm).Descriptive statistics for 16 agro-morphological characteristics in umte and tening groups clustered separately based on the phenotypic traits  using 16 traits produced five principal components  which cumulatively accounted for 76.4 % of the total phenotypic variance  of 15 tenning accessions which had highest values for KW, GrLW, DtF, LL and leaf width (LW).Ward’s hierarchical cluster analysis revealed a similar grouping of accessions as found in PCA Fig. . OverallHe) ranged from 0.41 (RM55) to 0.94 (RM259) and the average observed heterozygosity (Ho) was 0.051. Allelic richness (Rs) varied from 2.0 (RM338) to 14.6 (RM259) with an average value of 6.04 across the study. The polymorphism information content (PIC) values ranged from 0.37 (RM338 and RM507) up to 0.93 (RM259) with an average of 0.65.The summary statistics of 35 SSR markers are given in Additional file K values by increasing K from 1 to 8, we found that LnP(D) values increased with K, with the highest log likelihood score at K = 2, while ∆K value was also highest at K = 2  including ‘Azucena’, ‘TKM9’ and ‘Pakistani Basmati’ were identified in this group. Group 2 consisted of a total of 47 accessions including ‘Dular’, a japonica admixture variety, as admixture. At K = 3, ten control varieties  formed group 1 along with 11 hill accessions. Group 2 has 15 hill rices along with ‘Dular’ as admixture. A majority of hill rices (37 accessions) were included in group 3 along with the control varieties such as ‘Azucena’, ‘TKM9’, ‘Pakistani Basmati’ and ‘Mohanbhog’. The subpopulation structure in these rice accessions was more clear at K = 4. The four subpopulations (StrGr1 to 4) had a population-specific Fst value of 0.33, 0.33, 0.06 and 0.20, respectively, with an average of 0.23, indicating a moderate population structure. At this level, indica control varieties were separated from aus and aromatic varieties. The aromatic tropical japonica variety ‘Azucena’ showed separate grouping along with 50 % of hill accessions. A group of 15 hill accessions formed a distinct group (StrGr1). At K = 4, a total of 25 accessions were identified as an admixture.The inferred population structures are given in Fig. indica and aus controls, along with four hill accessions collected from Kurung Kumey and a single accession from East Kameng. Cluster 2 grouped all aromatic control varieties and four hill accessions collected from East Kameng. The rest hill rices grouped either with tropical japonica variety ‘Azucena’ (53 accessions) or with ‘Dular’ (3 accessions). The cluster membership of each accession is given in Additional file K = 4). However, the PCoA results were consistent with STRUCTURE  analysis of pair-wise genetic distances detected four major clusters  among and within subpopulation groups corresponding to districts, STRUCTURE groups and overall hill and control accessions  0.8 % of the total variation among umte and tening groups was recorded. Considering the districts, the highest genetic diversity was observed in East Kameng accessions (0.65) with a mean of 6.31 alleles per locus. The lowest genetic diversity was recorded in the accessions from Papum Pare (0.50) with a mean of 3.54 alleles per locus  was identical. The umte group had the highest PIC value in spite of having lower number of accessions. Among four STRUCTURE subpopulations, the highest genetic diversity was observed in StrGr3 (0.69) with an AN of 6.26, followed by StrGr4 (0.59) with an AN of 5.69. Similar trends were observed for PIC and allelic richness (Rs) values. The overall genetic diversity in hill and control accessions was at par, but the hill rices had the highest Rs (5.47) and AN (7.4). Note that, despite having only 15 accessions, the control group recorded the highest genetic diversity and PIC. This may be due to inclusion of diverse rice control varieties from different genetic groups.The rice accessions displayed different pattern of SSR variation with respect to district, cultivar group and STRUCTURE grouping Table . The AMOus Table . Betweenumte and tening, or between controls and either of the two groups. Among the four STRUCTURE subpopulations, allelic count of StrGr3 was significantly different with that of StrGr1 and StrGr2  is an important measure of diversity. Pair-wise tests of allelic differences between different groups of accessions are given in Fig. Gr2 Fig. . Pair-wiFst values among and between subpopulations are given in Additional file umte and tening was very low (0.008). Overall, the rice accessions from three districts had a low level of differentiation with Fst values ranging from 0.043 to 0.126. Among the STRUCTURE groups, the greatest differentiation was observed between StrGr1 and 2 (0.290), and the lowest was between StrGr3 and 4 (0.086).Pair-wise estimates of indica, aus, aromatic, tropical japonica and temperate japonica , followed by the indica (0.231) .We sampled 150 diverse rice cultivars representing all five major groups identified in previous studies , 28 to aica Fig. . The paiumte and tenning based on grain morphology and crop duration. These two groups of hill rice germplasm varied significantly for the traits such as plant height, leaf length, grain/kernel length and grain/kernel length-to-width ratio, but non-significant genetic differentiation between the two groups were observed. Population genetic analysis showed that these hill rices were mostly japonica or admixture among the subpopulations of Indica or Japonica. These results are useful for understanding the agro-morphological variability, genetic diversity and structure of hill rice landraces, and significant for utilization of hill rices in crop improvement programmes. Our study also provides baseline information for planning in-situ conservation of the hill rice landraces, which are adapted to local environments in harmony with cultural preferences of the farmers.Our characterization of hill rice germplasm of North-Eastern region of India has revealed that a diverse array of rice landraces was grown by the farmers which traditionally classified as pitha and sweets. Therefore, knowledge about the local names of rice landraces is useful for understanding their origin as well as grain quality and other characteristics. The traditional rice landraces possess wide genetic variability valuable for rice breeding [The traditional names of rice cultivars are generally found to be a valuable concept in describing the landraces worldwide. In the present study, the names of rice cultivars varied among the districts. Few rice accessions ‘Taba’, ‘Kilung’ and ‘Sarpung’ were cultivated in all three districts. The farmers in Arunachal Pradesh most often name the rice landraces after their place of origin. For instance, ‘Nepali dhan’ is originated in Nepal. Likewise, ‘Manipuri dhan’ and ‘Naga dhan’ are from the state of Manipur and Nagaland, respectively. Rice landraces often named after a community/tribe. For example, ‘Taba dugu’ and ‘Adi’ named after ‘Taba’ and ‘Adi’ communities of Arunachal Pradesh, respectively. During collection trip the farmers expressed that hill rice cultivars generally taste better than the low land cultivars, and thus used for making local delicacies like breeding , 43. Thebreeding . In Nepabreeding . It was breeding .umte and tening). Our analysis apparently showed that two groups of hill rice are mainly differentiated by the traits such as grain/kernel length and length-to-width ratio. We did not find significant variation in days to flowering between umte and tening. However, this is a key trait considered by the farmers in categorizing the hill rices. The non-significant variation in days to flowering in the present study may be due to change in crop growing conditions including soil and other environmental factors. We also performed a step-wise canonical discriminant analysis (CDA) taking umte and tening as priori groups to identify the most important discriminating traits contributing to the grouping of hill rices. Kernel length and plant height were found to be the best predictors for classifying the cultivar groups (results not shown). In both PCA and cluster analysis, we found that the accessions with similar names formed close groups, indicating the consistency in naming the cultivars by traditional farmers. However, in a different study with 130 indigenous rice accessions from a neighbouring state  in NE India, we found inconsistency in naming the cultivars [The tribal farmers of Arunachal Pradesh usually classify hill rice cultivars on the basis of grain morphology and/or quality characteristics, in addition to other agronomic traits such as crop duration. In the present study, we have assessed the variability in agronomic and grain/ kernel morphological traits to understand the morphological factors differentiating the two groups  and naming of rice cultivars. We cannot explain why geographical distribution did not match with genetic relationship among accessions. Seed exchange between the villages might be the reason. We noted that the farmers in Arunachal Pradesh most often gift seeds of good rice varieties during wedding ceremonies. It has been observed that the landraces with the same name collected from different villages/district are not always genetically identical. Similar observations were also reported in other studies , 48. TheHe = 0.66; PIC = 0.62) similar to the 107 aromatic rice cultivars of NE India  [umte and tening groups of hill rice was at par, and pair-wise allelic difference was non-significant. This is perhaps due to similar genetic makeup of the accessions of two morphological groups. The genetic diversity estimates among four STRUCTURE subpopulations were higher for group 3 and 4 , which can be categorized as japonica groups. However, the gene diversity in nine accessions of groups 2 was slightly lower (He = 0.53). This group was characterized by indica accessions, and higher genetic diversity of these accessions supports the fact that indica accessions are more diverse than japonica accessions [The current hill rice accessions revealed overall genetic diversity ( = 0.62) . Slightl = 0.62) . The gen = 0.62) . Althoug = 0.62) . The divcessions , 56.japonica or admixture among the subpopulations of Indica or Japonica. Both FPTest and Fst results indicated that the hill accessions are genetically diverse from temperate japonica and indica. The rice germplasm prevailing in NE India has great importance in studying the evolution and population genetics of cultivated rice. This region is considered to be the domestication origin of Indica rices [Japonica rice [Japonica rices has also been recorded in NE Indian rice germplasm [Indica-Japonica evolution.The present research, although with a limited number of SSR markers, indicated that hill rices were mostly ca rices . While, ica rice , 57. Theica rice . Prevaleermplasm , 59. TheThe findings presented here also have some implications for the utilization and conservation of hill rice germplasm. First, considerable diversity, both in agro-morphological and genetic terms, has been maintained by the traditional farmers. This is most likely the result of maintaining different sets of landraces in different regions in response to local heterogeneities in climate and soil type, as well as indigenous culture, as demonstrated by Fu et al.  in Thai AMOVA, analysis of molecular variance; AN, average number of alleles per locus; ANOVA, analysis of variance; CDA, canonical discriminant analysis; CGIAR, Consultative Group on International Agricultural Research; CV, coefficient of variation; ICAR, Indian Council of Agricultural research; MAF, major allele frequency; NJ, neighbour joining; PCA, principal component analysis; PCoA, principal coordinate analysis; PCR, polymerase chain reaction; PIC, polymorphism information content; SD, standard deviation; SSR, Simple sequence repeats