The 2010 paper  from Svante Pääbo’s group describing the draft Neanderthal nuclear genome—a seminal contribu- tion to our understanding of recent human evolution—was followed swiftly the same year by publication of the Deniso- van genome, which was arguably even more revelatory . Comparative analyses of these paleogenomes provided sur- prising but convincing evidence of reticulate gene flow and admixture between these archaic groups and anatomically modern humans during the Late Pleistocene [103, 105]. Additional Neanderthal and Denisovan genome sequence data have been assembled over the past decade, some of which are at sufficiently high depth for functional population genomics investigations of adaptive and maladaptive intro- gression into modern humanpopulations (for reviews see [129, 192–196]). It is now well established that people out- side of sub-Saharan Africa exhibit varying but consistently detectable genomic signatures of admixture with these ar- chaic hominins [82, 126, 129, 192, 194–196]. In addition, introgression of Neanderthal and Denisovan protein-coding gene segments and genomic regulatory elements (GREs) has had functional consequences, the textbook example being positive selection of a Denisovan haplotype of the endothelial PAS domain protein 1 gene (EPAS1) for altitude adaptation in Tibetan humanpopulations .
Over the past 100 years, the datasets and mathematical methodologies used in population genetics have changed enormously, providing an ever better understanding of human genetic diversity over time and space. In 1954, Arthur Mourant published his ground-breaking book “ The distribution of the human blood groups ” , probably the first full anthropological work to use a genetic perspective, showing that detectable genetic differences exist among different humanpopulations. Blood groups and protein types constitute what are now known as ‘ classical markers ’ and were used to compare humanpopulations for several decades, preceding the DNA-based datasets utilized today. The development of the polymerase chain reaction (PCR) in the 1980s introduced the use of molecular markers to population genetics and allowed, for the first time, the study of evolutionary distances between alleles at a locus. This methodological progress, along with theoretical advances such as identity by descent developed by Gustave Malécot in 1939  and coalescent theory developed by John Kingman in 1982 , provided an unprecedented understanding of the genetic relationships among humanpopulations, as well as their relatedness and divergence from other species.
While most ancienthuman genome data reported to date originate from European specimens, researchers have started exploring the population history of other populations as well (Figure 1). Thus, in January 2014, Raghavan et al.  presented the genome of an ap- proximately 24,000-year-old individual from Mal’ta in south-central Siberia, sequenced to an average coverage of 1×. Despite the low coverage, the genome provided evidence that Native Americans share a dual ancestry in- fluenced by genetic contributions from both eastern Asian and western Asian populations. These results con- firmed and expanded on earlier results based on modern genome data  which showed a signal of admixture into Northern Europe consisting of ancestral links to present day Basques and Sardinians as well as the north- east Asian/American component identified by Raghavan et al. . While at first sight it may seem surprising that low coverage genome data can provide such insights with any level of confidence, it becomes more under- standable when the total number of informative mutations used in these analyses is considered. Any one mutation characterising the ancestry of an ancient individual se- quenced to low coverage may be a result of sequencing error, but the study described above compared 66,285 single nucleotide polymorphisms (SNPs) to a reference panel of 1,301 individuals. Given the large number of markers characterising the ancestry of the individual, the chances that sequencing errors at known SNP sites alone result in incorrect ancestry inferences are therefore
with an asterisk. BLAST top hits for each dietary sequence are highlighted. The maximum fraction of mismatched bases is 0.75 for tree generation, and distance was calculated using a Jukes-Cantor substitution model. Tree scale bars indicate nucleotide substitutions per site. mtDNA, mitochondrial DNA. (d) One sequence aligned to two accessions of bread wheat only. (e–h) The microfossils recovered from ancienthuman dental calculus yielded morphological matches to animal collagen fibers (e), a smooth long-cell phytolith (f) and starch granules of the grass tribe Triticeae (g) and the legume family Fabaceae (h). Characteristic starch granule birefringence is shown under polarized light in the insets in g,h. Scale bars, 50 µm in e, 25 µm in f–h. (i) C and N stable isotopic values for human bone collagen (black circles) fall within 2 s.d. (boxes) of those measured for other Central European populations and are consistent with a diet of mixed C 3 terrestrial plant and animal resources. Isotopic values are reported in delta notation:
AncientDNA studies have documented a clean break between the genetic structure of the Mesolithic hunter–gatherers of Europe and the Neolithic ﬁrst farmers who followed them. Mitochondrial analyses have shown that the ﬁrst farmers in central Europe, belonging to the linear pottery culture (LBK), were genetically strongly differentiated from European hunter–gatherers (Bramanti et al. 2009), with an afﬁnity to present-day Near Eastern and Anatolian populations (Haak et al. 2010). More recently, new insight has come from anal- ysis of ancient nuclear DNA from three hunter–gatherers and one Neolithic farmer who lived roughly contemporaneously at about 5000 YBP in what is now Sweden (Skoglund et al. 2012). The farmer’s DNA shows a signal of genetic related- ness to Sardinians that is not present in the hunter–gatherers who have much more relatedness to present-day northern Europeans. These ﬁndings suggest that the arrival of agricul- ture in Europe involved massive movements of genes (not just culture) from the Near East to Europe and that people descending from the Near Eastern migrants initially reached as far north as Sweden with little mixing with the hunter– gatherers they encountered. However, the fact that today, northern Europeans have a strong signal of admixture of these two groups, as proven by this study and consistent with the ﬁndings of (Skoglund et al. 2012), indicates that these two ancestral groups subsequently mixed.
sublineage) may have dispersed outside Africa following the recent out-of-Africa migration of modern humans, while some expanded in one or more isolated hominin populations in Africa or became extinct. The MRCA for HPV58 non-A variants (358 kya; 95% HPD, 245 to 473 kya) seems older than the one for A variants (198 kya; 95% HPD, 122 to 283 kya) (Fig. 4 and Table 5), consistent with the low genomic diversity of A variants, probably because of a population bottleneck where only a proportion of viruses in Neanderthals/Denisovans was able to be horizontally transferred to modern humans. In contrast, HPV58 non-A variants are more diversiﬁed, matching the obser- vation that African populations were the most diverse populations genetically (32). This may also support the notion that both modern humans and HPV58 non-A variants arose in Africa. Besides, interbreeding between archaic hominins was multiregional, occurring at different times and places (29). For example, a subset of modern human ancestors who carried some Neanderthal DNA may have headed east and interbred with Denisovans in Oceania (e.g., Australia, Melanesia, and the Philippines) (33). Al- though the contribution of Denisovans to modern humans was quantitatively small, gene ﬂow from ancient Oceanians (after they mixed with Denisovans) to mainland Asian ancestors may have accumulated; as a result, certain viral variants (e.g., A1 and A3 sublineages) became more predominant in East Asia. While we were able to analyze the largest available worldwide collection of HPV58 isolates, the number of samples from certain areas is small, precluding a determination of the accurate geographic distribu- tion of viral variants in different geographic areas. For example, the history of B1 variants is still elusive. The B1 sublineage is closer to B2, but they cannot be classiﬁed in the same monophyletic clade (Fig. 1); independent evolutionary histories encom- passed by each of them may explain their differences in dispersal and frequency in present-day populations.
on the purpose of the experiment) is amplified two-fold at every heating (denaturation) and cooling (annealing) cycle in the lab (Appendix 3.1). The generation of PCR in genetics allowed for the development of ancientDNA analyses owing to the exponential copying of small or highly deteriorated fragments of DNA, which then allowed for the preservation, sequencing and analysis of that remnant sequence. Because morphological and modern genetic markers can only provide indirect evidence of evolutionary history (Willerslev and Cooper 2005), and with the success of E. quaagga DNA amplification (Higuchi et al. 1984), the field of paleo molecular genetics took off in the late 1980s, becoming especially relevant for archaeologists, paleoecologists and paleontologists. For the first time, aDNA (typically defined as DNA older than 100-200 years) allowed scientists to record genetic changes and evolutionary histories in real time and over short geological time-scales (Willerslev and Cooper 2005). However gene-sequencing took a hyperactive life of its own and soon laboratories all over the world were gene coding for a variety of organisms. Hofreiter (2012:1) recalls this period of ‘set backs’ in the early and mid-90s as something paleo geneticists are still dealing with today: “several high- impact publications that reported amplifications and analyses of DNA from many million year old samples […] later on turned out to have been based on contamination with modern DNA.”
Sediment DNA samples and all control samples were sub- jected to nested PCR amplification of the 28S rRNA gene using primers F63 (GCATATCAATAAGCGGAGGAAAAG) and R635 (GGTCCGTGTTTCAAGACGG), followed by CopF2 (TGTGTGGTGGTAAACGGAG) and CopR1 (CCGCCGACCTACTCG). Thermocycler conditions for the F63-R635 PCR comprised an initial denaturation step of 4 min at 94° C; 18 cycles of 94° C for 30 s, 62° C for 45 s (decreasing by 0.5° C each cycle), and 72° C for 60 s; 10 cycles of 94° C for 30 s, 52° C for 30 s, and 72° C for 60 s; and a final 72° C extension step of 4 min. For the CopF2-CopR1 PCR, the following thermocycler conditions were employed: 94° C for 60 s; 29 cycles of 94° C for 5 s, 61° C for 20 s, and 72° C for 30 s; and a final 72° C extension step of 10 min. All PCR products were subjected to electrophoresis on a 1% agarose gel stained with ethidium bromide to confirm the presence of DNA fragments of the correct length and to Table 3. Copepod species sequenced using the CopF2 and CopR1 primers. All lakes and bays mentioned specifically, with the excep- tion of Lake Terrasovoje, are in the Vestfold Hills, Antarctica. Samples from the Larsemann Hills were collected immediately offshore from China’s Zhong Shan research station.
Advances in sequencing and improved methods for the extraction of ancientDNA (aDNA) have enabled the study of ancient genomes. However, many computational hur- dles remain in the analysis of aDNA. After the death of an organism, the endogenous DNA begins to degrade and accumulates chemical damage. aDNA molecules, there- fore, tend to be quite short, typically less than 60 bases in length , and carry uracils as a result of cytosine deam- ination. Deaminated cytosines are misread as thymines during sequencing and lead to the characteristic increase in frequency of cytosine to thymine transitions near the ends of ancient molecules . Further, when extracting DNA from ancienthuman remains, microbial DNA often forms the bulk of all recoverable fragments , which, together with contaminating DNA from individuals who handled the ancient sample, is sequenced along with the endogenous DNA . While bacterial sequences do not typically align to the human reference genome, present- day human contaminants will align together with the
Plant fossil remains displaying the characteristics of domesticated cereal crops have been discovered at mul- tiple archaeological sites dating from 8000–10,000 years ago, a key historic period marking the human transition from a foraging lifestyle to early sedentary agricultural societies. The domestication of wheat involved selection for traits that are related to seed dormancy and disper- sal, such as brittle rachis, tenacious glume, and non- free-threshing traits . The spread outside of the ori- ginal domestication center followed four major historical routes of human migration, including a westwards ex- pansion through inland (via Anatolia and the Balkans to Central Europe) and coastal (via Egypt to the Mahgreb and Iberian peninsula) paths, and an eastwards expansion through the north and along the Inner Asian Mountain Corridor . Following domestication, modern breed- ing activities starting after 1850 CE (Common Era) further reduced the genetic diversity in genomic regions harbor- ing genes involved in agricultural performance or adapta- tion (such as photoperiodism, vernalization, flowering,
settings with the following exceptions: we subsampled large bam files to correspond with 1 Gigabyte input file ( ∼ 10–20 million reads with typical dataset complexity and a human genome) using the mapDamage ‘-n’ option. We analyzed the mapDamage Markov chain Monte Carlo (MCMC) out- put from each sample using the ‘coda’ R package (51) to estimate an effective sample size (ESS) for each of the six variables estimated by the mapDamage simulation. ESS val- ues are reported in Supplemental Dataset S1. We enforced a minimum ESS of 200 in all variables to ensure MCMC simulation convergence, excluding nine datasets for deam- ination analysis. For libraries with highly asymmetrical 3 and 5 C-to-T mismatch observed visually in misincorpora- tion plots, indicating the likely use of a non-proofreading DNA polymerase for library amplification––incapable of recovering uracils in template DNA––we re-ran mapDam- age with the ‘–reverse’ option to estimate damage from the 3 end only. We noted extremely high deamination and overhang termination values in the output from Mammoth M4 (7), which suggested a much higher rate of deami- nation than even much older permafrost samples. How- ever, that library is dominated by very short fragments (ref (7); summarized in the fragment length plot on Dryad), which we hypothesized could influence the mapDamage MCMC to over-estimate both parameters. We re-analyzed that sample considering only reads ≥ 40nt, yielding the dam- age parameter values reported in Dataset S1. Data from the Saqqaq Palaeo-Eskimo genome (32) were mostly gener- ated using a non-proofreading enzyme, but a small propor- tion of read files were reported to have been generated us- ing a proofreading Platinum High Fidelity Taq polymerase (22). We mapped all Saqqaq read files from the Sequence Read Archive (n = 218) to a human mitochondrial genome (EU256375.1), used PMDtools (52) to rapidly generate mis- incorporation plots and visually inspected each for elevated 5 C-to-T mismatch. This approach yielded two libraries apparently produced using a proofreading enzyme, one of which (SRR030983) was carried through for analysis. All mapDamage output files (run logs, plots, MCMC trace files and summary statistics) from the 185 final runs are available in the Dryad Digital Repository (see Availability below). Fi- nally, we summarized a deamination rate for each sample according to the equation:
To gain a complete, unbiased appraisal of the damage spectrum in both ancient nuclear and mitochondrial DNA, further studies should attempt to generate PCR products of the same length with an equal number of starting template molecules. Additionally, when design- ing PCR assays for ancient nuclear loci, restricting amplicon size will both increase the chance of successful amplification and maximize the number of starting template molecules. Importantly, sequence heteroge- neity in the clone data might in fact represent real allelic variation. In this study we cannot rule out that some sites interpreted as damaged might indeed represent real allelic differences (e.g., the fast-evolving CD45 gene seen in the pig data). For the moa data, however, one of the nuclear genes (kw1) is sex linked and therefore will have no allelic variation. Allelic variation in combination with low starting template numbers can also lead to cases of ‘‘allelic dropout’’ whereby one allelic form is amplified preferentially over another, which calls for reproduc- ibility of results (T aberlet et al. 1996; M orin et al. 2001). In the same way that nuclear mitochondrial insertions (numts) have caused the misinterpretation of mitochon- drial phylogenies (see W illerslev and C ooper 2005), nuclear pseudogenes and gene duplications can cause problems in the interpretation of nuDNA sequences. Complete genomes are now available for a variety of or- ganisms, making it possible to screen for the presence of duplicated genes. However, in cases where a genetic background is not well characterized, there is a consid-
The study of dermatoglyphic, hereditary characteristics, which take on their final form in about the fourth month of intra-uterine life, is a great help towards a better knowledge of the different humanpopulations Maxia, et al. . Of the different dermatoglyphic characteristics we choose in this work the terminations of the C line .In 1970, Plato classified the terminations of the C line (the main line departing from c triradius at the base of the ring finger, Cummins, et al.  into four modal types:
Sample collection. Sewage influent samples were collected from 71 cities and 78 wastewater treatment plant (WWTP) sites from across the United States during August 2012 (7 August 2012 to 7 September 2012), January 2013 (9 January 2013 to 28 February 2013), and May 2013 (28 April 2013 to 4 June 2013). To obtain these samples, we shipped sampling supplies to each of the WWTPs, including a cooler, frozen cold packs, sterile 500-ml sample bottles, chain-of-custody forms, and sample instructions. WWTP operators at each site collected sewage influent according to their plant’s standard collection procedures, which ranged from single-time-point grab samples to flow-weighted composite samples taken over a 24-h pe- riod (see Table S1 in the supplemental material for metadata details). Following sample collection, the operators transferred the influent to an autoclaved sample bottle and then placed the sample bottle in a refriger- ator until shipment to our lab. Prior to overnight shipping, the operators sealed the sample with Parafilm and placed the sample in the provided cooler containing frozen cold packs. Upon receiving sewage influent from the WWTPs, we mixed the influent by shaking and collected the microbial communities by filtration of 10 25-ml subsamples onto 0.22-m mixed cellulose ester filters (47-mm diameter; Millipore, Billerica, MA, USA). Each filter was stored in a 2-ml screw-cap freezer tube at ⫺ 80°C for up to 3 months before extraction of DNA. Using a sterile spatula, we crushed the frozen filters in their 2-ml storage tube and added a bead-beating matrix plus buffers according to the standard protocol for the Fast DNA spin kit for soil (MP Biomedicals, Solon, OH, USA). Following bead beating for 1 min, we extracted DNA according to the manufacturer’s instructions and purified sample DNA using the Mo Bio PowerClean DNA cleanup kit (Mo Bio Laboratories Inc., Carlsbad, CA, USA).
This brief presents recommendations created as part of the Research Development Project on the Human the knowledge base and research needs related to LGBT people’s socioeconomic circumstances and risk factors, their current participation in human services funded by the Administration for Children and Families (ACF) in the U.S. Department of Health and Human Services, and strategies for serving these populations effectively. Its methods included a literature review, analyses of secondary data sources, and consultations with experts and service providers.
appropriate. We have shown the geographic distribution of counties with high levels of human services needs, as defined by the top 10 percentile ranking of all counties for each of our eight demographic and four economic risk factors The type and number of risk factors present in metropolitan and non-metropolitan counties differs substantially with non-metropolitan counties more likely to have multiple risk factors present. This suggests that implementation strategies that are successful in metropolitan areas may not translate well to non-metropolitan areas. For example, a need for integrated human service delivery may be even more critical in non- metropolitan areas than metropolitan areas. Additionally, we have developed a conceptual framework that can be used at a geographic level to target intervention strategies to particular regions or particular human service needs.
Onion also found in Span western and eastern Asia, the geographic origin of the onion is uncertain, with likely domestication worldwide. Food uses of onions date back thousands of years in China, Egypt and Persia. Some Traces of onions found from Bronze. Age settlements in China recommend that onions were used as far back as 5000 BCE, not only for their flavor, but the bulb's durability in storage and transport. Ancient