human genetic variation

{{further|Recent human evolution}}

Causes of differences between individuals include independent assortment, the exchange of genes (crossing over and recombination) during reproduction (through meiosis) and various mutational events.

There are at least three reasons why genetic variation exists between populations. Natural selection may confer an adaptive advantage to individuals in a specific environment if an allele provides a competitive advantage. Alleles under selection are likely to occur only in those geographic regions where they confer an advantage. A second important process is genetic drift, which is the effect of random changes in the gene pool, under conditions where most mutations are neutral (that is, they do not appear to have any positive or negative selective effect on the organism). Finally, small migrant populations have statistical differences – called the founder effect – from the overall populations where they originated; when these migrants settle new areas, their descendant population typically differs from their population of origin: different genes predominate and it is less genetically diverse.

In humans, the main cause is genetic drift.{{Cite journal |last1=Ackermann |first1=R. R. |last2=Cheverud |first2=J. M. |date=2004-12-16 |title=Detecting genetic drift versus selection in human evolution |journal=Proceedings of the National Academy of Sciences |volume=101 |issue=52 |pages=17946–17951 |doi=10.1073/pnas.0405919102 |issn=0027-8424 |pmc=539739 |pmid=15604148|bibcode=2004PNAS..10117946A |doi-access=free }} Serial founder effects and past small population size (increasing the likelihood of genetic drift) may have had an important influence in neutral differences between populations.{{citation needed|date=February 2015}} The second main cause of genetic variation is due to the high degree of neutrality of most mutations. A small, but significant number of genes appear to have undergone recent natural selection, and these selective pressures are sometimes specific to one region.{{cite journal | vauthors = Guo J, Wu Y, Zhu Z, Zheng Z, Trzaskowski M, Zeng J, Robinson MR, Visscher PM, Yang J | title = Global genetic differentiation of complex traits shaped by natural selection in humans | journal = Nature Communications | volume = 9 | issue = 1 | pages = 1865 | date = May 2018 | pmid = 29760457 | pmc = 5951811 | doi = 10.1038/s41467-018-04191-y | bibcode = 2018NatCo...9.1865G }}{{cite journal | vauthors = Wang ET, Kodama G, Baldi P, Moyzis RK | title = Global landscape of recent inferred Darwinian selection for Homo sapiens | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 103 | issue = 1 | pages = 135–40 | date = January 2006 | pmid = 16371466 | pmc = 1317879 | doi = 10.1073/pnas.0509691102 | quote = By these criteria, 1.6% of Perlegen SNPs were found to exhibit the genetic architecture of selection. | bibcode = 2006PNAS..103..135W | doi-access = free }}

Genetic variation among humans occurs on many scales, from gross alterations in the human karyotype to single nucleotide changes.

{{cite journal | vauthors = Kidd JM, Cooper GM, Donahue WF, Hayden HS, Sampas N, Graves T, Hansen N, Teague B, Alkan C, Antonacci F, Haugen E, Zerr T, Yamada NA, Tsang P, Newman TL, Tüzün E, Cheng Z, Ebling HM, Tusneem N, David R, Gillett W, Phelps KA, Weaver M, Saranga D, Brand A, Tao W, Gustafson E, McKernan K, Chen L, Malig M, Smith JD, Korn JM, McCarroll SA, Altshuler DA, Peiffer DA, Dorschner M, Stamatoyannopoulos J, Schwartz D, Nickerson DA, Mullikin JC, Wilson RK, Bruhn L, Olson MV, Kaul R, Smith DR, Eichler EE | display-authors = 6 | title = Mapping and sequencing of structural variation from eight human genomes | journal = Nature | volume = 453 | issue = 7191 | pages = 56–64 | date = May 2008 | pmid = 18451855 | pmc = 2424287 | doi = 10.1038/nature06862 | bibcode = 2008Natur.453...56K }} Chromosome abnormalities are detected in 1 of 160 live human births. Apart from sex chromosome disorders, most cases of aneuploidy result in death of the developing fetus (miscarriage); the most common extra autosomal chromosomes among live births are 21, 18 and 13.{{cite journal | vauthors = Driscoll DA, Gross S | title = Clinical practice. Prenatal screening for aneuploidy | journal = The New England Journal of Medicine | volume = 360 | issue = 24 | pages = 2556–62 | date = June 2009 | pmid = 19516035 | doi = 10.1056/NEJMcp0900134 }}

Nucleotide diversity is the average proportion of nucleotides that differ between two individuals. As of 2004, the human nucleotide diversity was estimated to be 0.1%{{cite journal | vauthors = Jorde LB, Wooding SP | title = Genetic variation, classification and 'race' | journal = Nature Genetics | volume = 36 | issue = 11 Suppl | pages = S28–33 | date = November 2004 | pmid = 15508000 | doi = 10.1038/ng1435 | doi-access = free }} to 0.4% of base pairs.{{cite journal | vauthors = Tishkoff SA, Kidd KK | title = Implications of biogeography of human populations for 'race' and medicine | journal = Nature Genetics | volume = 36 | issue = 11 Suppl | pages = S21–7 | date = November 2004 | pmid = 15507999 | doi = 10.1038/ng1438 | doi-access = free }} In 2015, the 1000 Genomes Project, which sequenced one thousand individuals from 26 human populations, found that "a typical [individual] genome differs from the reference human genome at 4.1 million to 5.0 million sites … affecting 20 million bases of sequence"; the latter figure corresponds to 0.6% of total number of base pairs.{{cite journal | vauthors = Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA, Abecasis GR | display-authors = 6 | title = A global reference for human genetic variation | journal = Nature | volume = 526 | issue = 7571 | pages = 68–74 | date = October 2015 | pmid = 26432245 | pmc = 4750478 | doi = 10.1038/nature15393 | bibcode = 2015Natur.526...68T }} Nearly all (>99.9%) of these sites are small differences, either single nucleotide polymorphisms or brief insertions or deletions (indels) in the genetic sequence, but structural variations account for a greater number of base-pairs than the SNPs and indels.{{cite journal | vauthors = Mullaney JM, Mills RE, Pittard WS, Devine SE | title = Small insertions and deletions (INDELs) in human genomes | journal = Human Molecular Genetics | volume = 19 | issue = R2 | pages = R131–6 | date = October 2010 | pmid = 20858594 | pmc = 2953750 | doi = 10.1093/hmg/ddq400 }}

{{As of|2017}}, the Single Nucleotide Polymorphism Database (dbSNP), which lists SNP and other variants, listed 324 million variants found in sequenced human genomes.{{Cite web|url=https://ncbiinsights.ncbi.nlm.nih.gov/2017/05/08/dbsnps-human-build-150-has-doubled-the-amount-of-refsnp-records/|title=dbSNP's human build 150 has doubled the amount of RefSNP records!|author=NCBI |date=2017-05-08|website=NCBI Insights|access-date=2017-05-16}}

File:dna-SNP.svg

{{Main|Single nucleotide polymorphism}}

A single nucleotide polymorphism (SNP) is a difference in a single nucleotide between members of one species that occurs in at least 1% of the population. The 2,504 individuals characterized by the 1000 Genomes Project had 84.7 million SNPs among them. SNPs are the most common type of sequence variation, estimated in 1998 to account for 90% of all sequence variants.{{cite journal | vauthors = Collins FS, Brooks LD, Chakravarti A | title = A DNA polymorphism discovery resource for research on human genetic variation | journal = Genome Research | volume = 8 | issue = 12 | pages = 1229–31 | date = December 1998 | pmid = 9872978 | doi = 10.1101/gr.8.12.1229 | doi-access = free }} Other sequence variations are single base exchanges, deletions and insertions.{{cite journal | vauthors = Thomas PE, Klinger R, Furlong LI, Hofmann-Apitius M, Friedrich CM | title = Challenges in the association of human single nucleotide polymorphism mentions with unique database identifiers | journal = BMC Bioinformatics | volume = 12 | pages = S4 | year = 2011 | issue = Suppl 4 | pmid = 21992066 | pmc = 3194196 | doi = 10.1186/1471-2105-12-S4-S4 | doi-access = free }} SNPs occur on average about every 100 to 300 bases{{cite journal | vauthors = Ke X, Taylor MS, Cardon LR | title = Singleton SNPs in the human genome and implications for genome-wide association studies | journal = European Journal of Human Genetics | volume = 16 | issue = 4 | pages = 506–15 | date = April 2008 | pmid = 18197193 | doi = 10.1038/sj.ejhg.5201987 | doi-access = free }} and so are the major source of heterogeneity.

A functional, or non-synonymous, SNP is one that affects some factor such as gene splicing or messenger RNA, and so causes a phenotypic difference between members of the species. About 3% to 5% of human SNPs are functional (see International HapMap Project). Neutral, or synonymous SNPs are still useful as genetic markers in genome-wide association studies, because of their sheer number and the stable inheritance over generations.

A coding SNP is one that occurs inside a gene. There are 105 Human Reference SNPs that result in premature stop codons in 103 genes. This corresponds to 0.5% of coding SNPs. They occur due to segmental duplication in the genome. These SNPs result in loss of protein, yet all these SNP alleles are common and are not purified in negative selection.{{cite journal | vauthors = Ng PC, Levy S, Huang J, Stockwell TB, Walenz BP, Li K, Axelrod N, Busam DA, Strausberg RL, Venter JC | display-authors = 6 | title = Genetic variation in an individual human exome | journal = PLOS Genetics | volume = 4 | issue = 8 | pages = e1000160 | date = August 2008 | pmid = 18704161 | pmc = 2493042 | doi = 10.1371/journal.pgen.1000160 | editor1-last = Schork | editor1-first = Nicholas J | doi-access = free }}

{{Main|Structural variation}}

Structural variation is the variation in structure of an organism's chromosome. Structural variations, such as copy-number variation and deletions, inversions, insertions and duplications, account for much more human genetic variation than single nucleotide diversity. This was concluded in 2007 from analysis of the diploid full sequences of the genomes of two humans: Craig Venter and James D. Watson. This added to the two haploid sequences which were amalgamations of sequences from many individuals, published by the Human Genome Project and Celera Genomics respectively.{{cite journal | vauthors = Gross L | title = A new human genome sequence paves the way for individualized genomics | journal = PLOS Biology | volume = 5 | issue = 10 | pages = e266 | date = October 2007 | pmid = 20076646 | pmc = 1964778 | doi = 10.1371/journal.pbio.0050266 | doi-access = free }}

According to the 1000 Genomes Project, a typical human has 2,100 to 2,500 structural variations, which include approximately 1,000 large deletions, 160 copy-number variants, 915 Alu insertions, 128 L1 insertions, 51 SVA insertions, 4 NUMTs, and 10 inversions.

{{Main|Copy number variation}}

A copy-number variation (CNV) is a difference in the genome due to deleting or duplicating large regions of DNA on some chromosome. It is estimated that 0.4% of the genomes of unrelated humans differ with respect to copy number. When copy number variation is included, human-to-human genetic variation is estimated to be at least 0.5% (99.5% similarity).{{cite web

|date=3 September 2007

|title=First Individual Diploid Human Genome Published By Researchers at J. Craig Venter Institute

|url=http://www.jcvi.org/cms/press/press-releases/full-text/article/first-individual-diploid-human-genome-published-by-researchers-at-j-craig-venter-institute/

|publisher=J. Craig Venter Institute

|access-date=2011-09-05

|archive-url=https://web.archive.org/web/20110716022944/http://www.jcvi.org/cms/press/press-releases/full-text/article/first-individual-diploid-human-genome-published-by-researchers-at-j-craig-venter-institute/

|archive-date=16 July 2011

|url-status=dead

}}

{{cite journal | vauthors = Levy S, Sutton G, Ng PC, Feuk L, Halpern AL, Walenz BP, Axelrod N, Huang J, Kirkness EF, Denisov G, Lin Y, MacDonald JR, Pang AW, Shago M, Stockwell TB, Tsiamouri A, Bafna V, Bansal V, Kravitz SA, Busam DA, Beeson KY, McIntosh TC, Remington KA, Abril JF, Gill J, Borman J, Rogers YH, Frazier ME, Scherer SW, Strausberg RL, Venter JC | display-authors = 6 | title = The diploid genome sequence of an individual human | journal = PLOS Biology | volume = 5 | issue = 10 | pages = e254 | date = September 2007 | pmid = 17803354 | pmc = 1964779 | doi = 10.1371/journal.pbio.0050254 | doi-access = free }}{{cite web

|date=24 January 2008

|title=Understanding Genetics: Human Health and the Genome

|url=http://www.thetech.org/genetics/news.php?id=74

|publisher=The Tech Museum of Innovation

|access-date=2011-09-05

|archive-date=29 April 2012

|archive-url=https://web.archive.org/web/20120429102022/http://www.thetech.org/genetics/news.php?id=74

|url-status=dead

}}

{{cite web

|url=https://www.sciencedaily.com/releases/2007/09/070904072204.htm

|title=First Diploid Human Genome Sequence Shows We're Surprisingly Different

|publisher=Science Daily

|date=4 September 2007

|access-date=2011-09-05

}} Copy number variations are inherited but can also arise during development.

{{cite web

|url=http://www.eurekalert.org/pub_releases/2007-12/bcom-cnv122607.php

|title=Copy number variation may stem from replication misstep

|publisher=EurekAlert!

|date=27 December 2007

|access-date=2011-09-05

}}

{{cite journal | vauthors = Lee JA, Carvalho CM, Lupski JR | title = A DNA replication mechanism for generating nonrecurrent rearrangements associated with genomic disorders | journal = Cell | volume = 131 | issue = 7 | pages = 1235–47 | date = December 2007 | pmid = 18160035 | doi = 10.1016/j.cell.2007.11.037 | s2cid = 9263608 | doi-access = free }}

{{cite journal | vauthors = Redon R, Ishikawa S, Fitch KR, Feuk L, Perry GH, Andrews TD, Fiegler H, Shapero MH, Carson AR, Chen W, Cho EK, Dallaire S, Freeman JL, González JR, Gratacòs M, Huang J, Kalaitzopoulos D, Komura D, MacDonald JR, Marshall CR, Mei R, Montgomery L, Nishimura K, Okamura K, Shen F, Somerville MJ, Tchinda J, Valsesia A, Woodwark C, Yang F, Zhang J, Zerjal T, Zhang J, Armengol L, Conrad DF, Estivill X, Tyler-Smith C, Carter NP, Aburatani H, Lee C, Jones KW, Scherer SW, Hurles ME | display-authors = 6 | title = Global variation in copy number in the human genome | journal = Nature | volume = 444 | issue = 7118 | pages = 444–54 | date = November 2006 | pmid = 17122850 | pmc = 2669898 | doi = 10.1038/nature05329 | bibcode = 2006Natur.444..444R }}

{{cite journal | vauthors = Dumas L, Kim YH, Karimpour-Fard A, Cox M, Hopkins J, Pollack JR, Sikela JM | display-authors = 6 | title = Gene copy number variation spanning 60 million years of human and primate evolution | journal = Genome Research | volume = 17 | issue = 9 | pages = 1266–77 | date = September 2007 | pmid = 17666543 | pmc = 1950895 | doi = 10.1101/gr.6557307 }}

A visual map with the regions with high genomic variation of the modern-human reference assembly relatively to a

Neanderthal of 50k{{cite journal | vauthors = Prüfer K, Racimo F, Patterson N, Jay F, Sankararaman S, Sawyer S, Heinze A, Renaud G, Sudmant PH, de Filippo C, Li H, Mallick S, Dannemann M, Fu Q, Kircher M, Kuhlwilm M, Lachmann M, Meyer M, Ongyerth M, Siebauer M, Theunert C, Tandon A, Moorjani P, Pickrell J, Mullikin JC, Vohr SH, Green RE, Hellmann I, Johnson PL, Blanche H, Cann H, Kitzman JO, Shendure J, Eichler EE, Lein ES, Bakken TE, Golovanova LV, Doronichev VB, Shunkov MV, Derevianko AP, Viola B, Slatkin M, Reich D, Kelso J, Pääbo S | display-authors = 6 | title = The complete genome sequence of a Neanderthal from the Altai Mountains | journal = Nature | volume = 505 | issue = 7481 | pages = 43–9 | date = January 2014 | pmid = 24352235 | pmc = 4031459 | doi = 10.1038/nature12886 | bibcode = 2014Natur.505...43P }} has been built by Pratas et al.{{cite book| vauthors = Pratas D, Hosseini M, Silva R, Pinho A, Ferreira P |title=Pattern Recognition and Image Analysis|chapter=Visualization of Distinct DNA Regions of the Modern Human Relatively to a Neanderthal Genome|volume=10255|pages=235–242|date=20–23 June 2017|doi=10.1007/978-3-319-58838-4_26|series=Lecture Notes in Computer Science|isbn=978-3-319-58837-7}}

Epigenetic variation is variation in the chemical tags that attach to DNA and affect how genes get read. The tags, "called epigenetic markings, act as switches that control how genes can be read."{{cite web

|date=19 August 2011

|title=Human Genetic Variation Fact Sheet

|url=http://www.nigms.nih.gov/Publications/Factsheet_GeneticVariation.htm

|publisher=National Institute of General Medical Sciences

|access-date=2011-09-05

|archive-date=16 September 2008

|archive-url=https://web.archive.org/web/20080916091604/http://www.nigms.nih.gov/Publications/Factsheet_GeneticVariation.htm

|url-status=dead

}} At some alleles, the epigenetic state of the DNA, and associated phenotype, can be inherited across generations of individuals.

{{cite journal | vauthors = Rakyan V, Whitelaw E | title = Transgenerational epigenetic inheritance | journal = Current Biology | volume = 13 | issue = 1 | pages = R6 | date = January 2003 | pmid = 12526754 | doi = 10.1016/S0960-9822(02)01377-5 | doi-access = free | bibcode = 2003CBio...13...R6R }}

{{Main|Genetic variability}}

Genetic variability is a measure of the tendency of individual genotypes in a population to vary (become different) from one another. Variability is different from genetic diversity, which is the amount of variation seen in a particular population. The variability of a trait is how much that trait tends to vary in response to environmental and genetic influences.

{{Main|Cline (biology)}}

In biology, a cline is a continuum of species, populations, varieties, or forms of organisms that exhibit gradual phenotypic and/or genetic differences over a geographical area, typically as a result of environmental heterogeneity.

{{cite encyclopedia

|year=2009

|title=Cline

|encyclopedia=Microsoft Encarta Premium

}}

{{cite book

| vauthors = King RC, Stansfield WD, Mulligan PK

|chapter=Cline

|title=A dictionary of genetics

| url = https://archive.org/details/dictionaryofplan0000unse_a2q0

| url-access = registration

|edition=7th

|year=2006

|publisher=Oxford University Press

|isbn=978-0195307610

}}

{{cite book

| vauthors = Begon M, Townsend CR, Harper JL

|year=2006

|title=Ecology: From individuals to ecosystems

|edition=4th |page=10

|publisher=Wiley-Blackwell

|isbn=978-1405111171

}} In the scientific study of human genetic variation, a gene cline can be rigorously defined and subjected to quantitative metrics.

{{Main|Haplogroup}}

In the study of molecular evolution, a haplogroup is a group of similar haplotypes that share a common ancestor with a single nucleotide polymorphism (SNP) mutation. The study of haplogroups provides information about ancestral origins dating back thousands of years.{{cite web |title=Haplogroup |url=https://isogg.org/wiki/Haplogroup |publisher=International Society of Genetic Genealogy |work=DNA-Newbie Glossary |access-date=2012-09-05}}

The most commonly studied human haplogroups are Y-chromosome (Y-DNA) haplogroups and mitochondrial DNA (mtDNA) haplogroups, both of which can be used to define genetic populations. Y-DNA is passed solely along the patrilineal line, from father to son, while mtDNA is passed down the matrilineal line, from mother to both daughter or son. The Y-DNA and mtDNA may change by chance mutation at each generation.

{{Main|Variable number tandem repeat}}

A variable number tandem repeat (VNTR) is the variation of length of a tandem repeat. A tandem repeat is the adjacent repetition of a short nucleotide sequence. Tandem repeats exist on many chromosomes, and their length varies between individuals. Each variant acts as an inherited allele, so they are used for personal or parental identification. Their analysis is useful in genetics and biology research, forensics, and DNA fingerprinting.

Short tandem repeats (about 5 base pairs) are called microsatellites, while longer ones are called minisatellites.

File:World map of prehistoric human migrations.jpg. Colored rings indicate thousand years before present.]]

File:Genetic similarities between 51 worldwide human populations (Euclidean genetic distance using 289,160 SNPs).png

{{See also|Human evolutionary genetics#Modern humans|Recent human evolution}}

The recent African origin of modern humans paradigm assumes the dispersal of non-African populations of anatomically modern humans after 70,000 years ago. Dispersal within Africa occurred significantly earlier, at least 130,000 years ago. The "out of Africa" theory originates in the 19th century, as a tentative suggestion in Charles Darwin's Descent of Man,{{cite web | url = http://darwin-online.org.uk/content/frameset?viewtype=text&itemID=F937.1&pageseq=212 | title = The descent of man Chapter 6 – On the Affinities and Genealogy of Man | publisher = Darwin-online.org.uk | access-date = 11 January 2011 | quote = In each great region of the world the living mammals are closely related to the extinct species of the same region. It is, therefore, probable that Africa was formerly inhabited by extinct apes closely allied to the gorilla and chimpanzee; and as these two species are now man's nearest allies, it is somewhat more probable that our early progenitors lived on the African continent than elsewhere. But it is useless to speculate on this subject, for an ape nearly as large as a man, namely the Dryopithecus of Lartet, which was closely allied to the anthropomorphous Hylobates, existed in Europe during the Upper Miocene period; and since so remote a period the earth has certainly undergone many great revolutions, and there has been ample time for migration on the largest scale. }} but remained speculative until the 1980s when it was supported by the study of present-day mitochondrial DNA, combined with evidence from physical anthropology of archaic specimens.

According to a 2000 study of Y-chromosome sequence variation,{{cite journal | vauthors = Underhill PA, Shen P, Lin AA, Jin L, Passarino G, Yang WH, Kauffman E, Bonné-Tamir B, Bertranpetit J, Francalacci P, Ibrahim M, Jenkins T, Kidd JR, Mehdi SQ, Seielstad MT, Wells RS, Piazza A, Davis RW, Feldman MW, Cavalli-Sforza LL, Oefner PJ | display-authors = 6 | title = Y chromosome sequence variation and the history of human populations | journal = Nature Genetics | volume = 26 | issue = 3 | pages = 358–61 | date = November 2000 | pmid = 11062480 | doi = 10.1038/81685 | s2cid = 12893406 }} human Y-chromosomes trace ancestry to Africa, and the descendants of the derived lineage left Africa and eventually were replaced by archaic human Y-chromosomes in Eurasia. The study also shows that a minority of contemporary populations in East Africa and the Khoisan are the descendants of the most ancestral patrilineages of anatomically modern humans that left Africa 35,000 to 89,000 years ago. Other evidence supporting the theory is that variations in skull measurements decrease with distance from Africa at the same rate as the decrease in genetic diversity. Human genetic diversity decreases in native populations with migratory distance from Africa, and this is thought to be due to bottlenecks during human migration, which are events that temporarily reduce population size.{{cite web |date=19 July 2007 |title=New Research Proves Single Origin of Humans in Africa |url=https://www.sciencedaily.com/releases/2007/07/070718140829.htm |publisher=Science Daily |access-date=2011-09-05}}{{cite journal | vauthors = Manica A, Amos W, Balloux F, Hanihara T|author-link3=Francois Balloux | title = The effect of ancient population bottlenecks on human phenotypic variation | journal = Nature | volume = 448 | issue = 7151 | pages = 346–8 | date = July 2007 | pmid = 17637668 | pmc = 1978547 | doi = 10.1038/nature05951 | bibcode = 2007Natur.448..346M }}

A 2009 genetic clustering study, which genotyped 1327 polymorphic markers in various African populations, identified six ancestral clusters. The clustering corresponded closely with ethnicity, culture and language.{{cite journal | vauthors = Tishkoff SA, Reed FA, Friedlaender FR, Ehret C, Ranciaro A, Froment A, Hirbo JB, Awomoyi AA, Bodo JM, Doumbo O, Ibrahim M, Juma AT, Kotze MJ, Lema G, Moore JH, Mortensen H, Nyambo TB, Omar SA, Powell K, Pretorius GS, Smith MW, Thera MA, Wambebe C, Weber JL, Williams SM | display-authors = 6 | title = The genetic structure and history of Africans and African Americans | journal = Science | volume = 324 | issue = 5930 | pages = 1035–44 | date = May 2009 | pmid = 19407144 | pmc = 2947357 | doi = 10.1126/science.1172257 | url = http://faculty.washington.edu/wjs18/Pop_Structure/TishkoffAfrican.pdf | bibcode = 2009Sci...324.1035T | quote = We incorporated geographic data into a Bayesian clustering analysis, assuming no admixture (TESS software) (25) and distinguished six clusters within continental Africa (Fig. 5A). The most geographically widespread cluster (orange) extends from far Western Africa (the Mandinka) through central Africa to the Bantu speakers of South Africa (the Venda and Xhosa) and corresponds to the distribution of the Niger-Kordofanian language family, possibly reflecting the spread of Bantu-speaking populations from near the Nigerian/Cameroon highlands across eastern and southern Africa within the past 5000 to 3000 years (26,27). Another inferred cluster includes the Pygmy and SAK populations (green), with a noncontiguous geographic distribution in central and southeastern Africa, consistent with the STRUCTURE (Fig. 3) and phylogenetic analyses (Fig. 1). Another geographically contiguous cluster extends across northern Africa (blue) into Mali (the Dogon), Ethiopia, and northern Kenya. With the exception of the Dogon, these populations speak an Afroasiatic language. Chadic-speaking and Nilo-Saharan–speaking populations from Nigeria, Cameroon, and central Chad, as well as several Nilo-Saharan–speaking populations from southern Sudan, constitute another cluster (red). Nilo-Saharan and Cushitic speakers from the Sudan, Kenya, and Tanzania, as well as some of the Bantu speakers from Kenya, Tanzania, and Rwanda (Hutu/Tutsi), constitute another cluster (purple), reflecting linguistic evidence for gene flow among these populations over the past ~5000 years (28,29). Finally, the Hadza are the sole constituents of a sixth cluster (yellow), consistent with their distinctive genetic structure identified by PCA and STRUCTURE. }} A 2018 whole genome sequencing study of the world's populations observed similar clusters among the populations in Africa. At K=9, distinct ancestral components defined the Afroasiatic-speaking populations inhabiting North Africa and Northeast Africa; the Nilo-Saharan-speaking populations in Northeast Africa and East Africa; the Ari populations in Northeast Africa; the Niger-Congo-speaking populations in West-Central Africa, West Africa, East Africa and Southern Africa; the Pygmy populations in Central Africa; and the Khoisan populations in Southern Africa.{{cite journal | vauthors = Schlebusch CM, Jakobsson M | title = Tales of Human Migration, Admixture, and Selection in Africa | journal = Annual Review of Genomics and Human Genetics | volume = 19 | pages = 405–428 | date = August 2018 | pmid = 29727585 | doi = 10.1146/annurev-genom-083117-021759 | s2cid = 19155657 | url = http://docdro.id/C0L2mMo | access-date = 28 May 2018 | doi-access = free }}

In May 2023, scientists reported, based on genetic studies, a more complicated pathway of human evolution than previously understood. According to the studies, humans evolved from different places and times in Africa, instead of from a single location and period of time.{{cite news |last=Zimmer |first=Carl |authorlink=Carl Zimmer |title=Study Offers New Twist in How the First Humans Evolved – A new genetic analysis of 290 people suggests that humans emerged at various times and places in Africa. |url=https://www.nytimes.com/2023/05/17/science/human-origins-africa.html |date=17 May 2023 |work=The New York Times |url-status=live |archiveurl=https://archive.today/20230517235653/https://www.nytimes.com/2023/05/17/science/human-origins-africa.html |archivedate=17 May 2023 |accessdate=18 May 2023 }}{{cite journal |author=Ragsdale, Aaron P. |display-authors=et al.|title=A weakly structured stem for human origins in Africa |date=17 May 2023 |journal=Nature |volume=167 |issue=7962 |pages=755–763 |doi=10.1038/s41586-023-06055-y |pmid=37198480 |pmc=10208968 |bibcode=2023Natur.617..755R }}

{{See also|Population genetics}}

Because of the common ancestry of all humans, only a small number of variants have large differences in frequency between populations. However, some rare variants in the world's human population are much more frequent in at least one population (more than 5%).{{cite journal | vauthors = Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA, Abecasis GR | display-authors = 6 | collaboration = 1000 Genomes Project Consortium | title = A global reference for human genetic variation | journal = Nature | volume = 526 | issue = 7571 | pages = 68–74 | date = October 2015 | pmid = 26432245 | pmc = 4750478 | doi = 10.1038/nature15393 | bibcode = 2015Natur.526...68T }}

File:Genetic Variation.jpgFile:Genetic distances Eurasian West Asian East Asian.png

It is commonly assumed that early humans left Africa, and thus must have passed through a population bottleneck before their African-Eurasian divergence around 100,000 years ago (ca. 3,000 generations). The rapid expansion of a previously small population has two important effects on the distribution of genetic variation. First, the so-called founder effect occurs when founder populations bring only a subset of the genetic variation from their ancestral population. Second, as founders become more geographically separated, the probability that two individuals from different founder populations will mate becomes smaller. The effect of this assortative mating is to reduce gene flow between geographical groups and to increase the genetic distance between groups.{{Citation needed|date=December 2017}}

The expansion of humans from Africa affected the distribution of genetic variation in two other ways. First, smaller (founder) populations experience greater genetic drift because of increased fluctuations in neutral polymorphisms. Second, new polymorphisms that arose in one group were less likely to be transmitted to other groups as gene flow was restricted.{{Citation needed|date=December 2017}}

Populations in Africa tend to have lower amounts of linkage disequilibrium than do populations outside Africa, partly because of the larger size of human populations in Africa over the course of human history and partly because the number of modern humans who left Africa to colonize the rest of the world appears to have been relatively low.{{cite journal | vauthors = Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, Liu-Cordero SN, Rotimi C, Adeyemo A, Cooper R, Ward R, Lander ES, Daly MJ, Altshuler D | display-authors = 6 | title = The structure of haplotype blocks in the human genome | journal = Science | volume = 296 | issue = 5576 | pages = 2225–9 | date = June 2002 | pmid = 12029063 | doi = 10.1126/science.1069424 | bibcode = 2002Sci...296.2225G | s2cid = 10069634 | doi-access = free }} In contrast, populations that have undergone dramatic size reductions or rapid expansions in the past and populations formed by the mixture of previously separate ancestral groups can have unusually high levels of linkage disequilibrium

File:Human genetic isolation by distance in Kanitz 2018.png loci taken from 1484 individuals in 78 human populations. The upper graph illustrates that as populations are further from East Africa, they have declining genetic diversity as measured in average number of microsatellite repeats at each of the loci. The bottom chart illustrates isolation by distance. Populations with a greater distance between them are more dissimilar (as measured by the Fst statistic) than those which are geographically close to one another. The horizontal axis of both charts is geographic distance as measured along likely routes of human migration. (Chart from Kanitz et al. 2018)]]

The distribution of genetic variants within and among human populations are impossible to describe succinctly because of the difficulty of defining a "population," the clinal nature of variation, and heterogeneity across the genome (Long and Kittles 2003). In general, however, an average of 85% of genetic variation exists within local populations, ~7% is between local populations within the same continent, and ~8% of variation occurs between large groups living on different continents.{{cite journal | vauthors = Bamshad MJ, Wooding S, Watkins WS, Ostler CT, Batzer MA, Jorde LB | title = Human population genetic structure and inference of group membership | journal = American Journal of Human Genetics | volume = 72 | issue = 3 | pages = 578–89 | date = March 2003 | pmid = 12557124 | pmc = 1180234 | doi = 10.1086/368061 }} The recent African origin theory for humans would predict that in Africa there exists a great deal more diversity than elsewhere and that diversity should decrease the further from Africa a population is sampled.

{{Further|Phenotype#Phenotypic variation}}

Sub-Saharan Africa has the most human genetic diversity and the same has been shown to hold true for phenotypic variation in skull form.Manica, Andrea, William Amos, François Balloux, and Tsunehiko Hanihara. "The Effect of Ancient Population Bottlenecks on Human Phenotypic Variation". Nature 448, no. 7151 (July 2007): 346–48. {{doi|10.1038/nature05951}}. Phenotype is connected to genotype through gene expression. Genetic diversity decreases smoothly with migratory distance from that region, which many scientists believe to be the origin of modern humans, and that decrease is mirrored by a decrease in phenotypic variation. Skull measurements are an example of a physical attribute whose within-population variation decreases with distance from Africa.

The distribution of many physical traits resembles the distribution of genetic variation within and between human populations (American Association of Physical Anthropologists 1996; Keita and Kittles 1997). For example, ~90% of the variation in human head shapes occurs within continental groups, and ~10% separates groups, with a greater variability of head shape among individuals with recent African ancestors (Relethford 2002).

A prominent exception to the common distribution of physical characteristics within and among groups is skin color. Approximately 10% of the variance in skin color occurs within groups, and ~90% occurs between groups (Relethford 2002). This distribution of skin color and its geographic patterning – with people whose ancestors lived predominantly near the equator having darker skin than those with ancestors who lived predominantly in higher latitudes – indicate that this attribute has been under strong selective pressure. Darker skin appears to be strongly selected for in equatorial regions to prevent sunburn, skin cancer, the photolysis of folate, and damage to sweat glands.{{cite book |last=Jablonski |first=Nina G. | name-list-style = vanc |title=Living Color: The Biological and Social Meaning of Skin Color |url=https://books.google.com/books?id=Jw7loAEACAAJ |date=10 January 2014 |publisher=University of California Press |isbn=978-0-520-28386-2 |jstor=10.1525/j.ctt1pn64b |chapter=The Biological and Social Meaning of Skin Color }}

Understanding how genetic diversity in the human population impacts various levels of gene expression is an active area of research. While earlier studies focused on the relationship between DNA variation and RNA expression, more recent efforts are characterizing the genetic control of various aspects of gene expression including chromatin states,{{cite journal | vauthors = Grubert F, Zaugg JB, Kasowski M, Ursu O, Spacek DV, Martin AR, Greenside P, Srivas R, Phanstiel DH, Pekowska A, Heidari N, Euskirchen G, Huber W, Pritchard JK, Bustamante CD, Steinmetz LM, Kundaje A, Snyder M | display-authors = 6 | title = Genetic Control of Chromatin States in Humans Involves Local and Distal Chromosomal Interactions | journal = Cell | volume = 162 | issue = 5 | pages = 1051–65 | date = August 2015 | pmid = 26300125 | pmc = 4556133 | doi = 10.1016/j.cell.2015.07.048 }} translation,

{{cite journal | vauthors = Cenik C, Cenik ES, Byeon GW, Grubert F, Candille SI, Spacek D, Alsallakh B, Tilgner H, Araya CL, Tang H, Ricci E, Snyder MP | display-authors = 6 | title = Integrative analysis of RNA, translation, and protein levels reveals distinct regulatory variation across humans | journal = Genome Research | volume = 25 | issue = 11 | pages = 1610–21 | date = November 2015 | pmid = 26297486 | pmc = 4617958 | doi = 10.1101/gr.193342.115 }} and protein levels.{{cite journal | vauthors = Wu L, Candille SI, Choi Y, Xie D, Jiang L, Li-Pook-Than J, Tang H, Snyder M | title = Variation and genetic control of protein abundance in humans | journal = Nature | volume = 499 | issue = 7456 | pages = 79–82 | date = July 2013 | pmid = 23676674 | pmc = 3789121 | doi = 10.1038/nature12223 | bibcode = 2013Natur.499...79W }} A study published in 2007 found that 25% of genes showed different levels of gene expression between populations of European and Asian descent.{{cite web

|vauthors=Phillips ML

|date=9 January 2007

|title=Ethnicity tied to gene expression

|url=http://classic.the-scientist.com/?articles.view/articleNo/24657/

|archive-url=https://archive.today/20150508183458/http://classic.the-scientist.com/?articles.view/articleNo/24657/

|url-status=dead

|archive-date=8 May 2015

|work=The Scientist

|access-date=2011-09-05

}}

{{cite journal | vauthors = Spielman RS, Bastone LA, Burdick JT, Morley M, Ewens WJ, Cheung VG | title = Common genetic variants account for differences in gene expression among ethnic groups | journal = Nature Genetics | volume = 39 | issue = 2 | pages = 226–31 | date = February 2007 | pmid = 17206142 | pmc = 3005333 | doi = 10.1038/ng1955 }}

{{cite web

|vauthors = Swaminathan N

|date=9 January 2007

|url=http://www.scientificamerican.com/article.cfm?id=ethnic-differences-traced

|title=Ethnic Differences Traced to Variable Gene Expression

|work=Scientific American

|access-date=2011-09-05

}}

{{cite journal

| vauthors = Check E

|year=2007

|title=Genetic expression speaks as loudly as gene type

|journal=Nature News

|doi=10.1038/news070101-8

|s2cid=84380725

}}{{cite web

|vauthors=Bell L

|date=15 January 2007

|url=http://www.bionews.org.uk/page_12961.asp

|title=Variable gene expression seen in different ethnic groups

|work=BioNews.org

|access-date=2011-09-05

|archive-date=26 March 2016

|archive-url=https://web.archive.org/web/20160326105441/http://www.bionews.org.uk/page_12961.asp

|url-status=dead

}} The primary cause of this difference in gene expression was thought to be SNPs in gene regulatory regions of DNA. Another study published in 2007 found that approximately 83% of genes were expressed at different levels among individuals and about 17% between populations of European and African descent.{{cite web

|vauthors=Kamrani K

|date=28 February 2008

|url=http://anthropology.net/2008/02/29/differences-of-gene-expression-between-human-populations/

|title=Differences of gene expression between human populations

|publisher=Anthropology.net

|access-date=2011-09-05

|archive-date=30 September 2011

|archive-url=https://web.archive.org/web/20110930163052/http://anthropology.net/2008/02/29/differences-of-gene-expression-between-human-populations/

|url-status=dead

}}

{{cite journal | vauthors = Storey JD, Madeoy J, Strout JL, Wurfel M, Ronald J, Akey JM | title = Gene-expression variation within and among human populations | journal = American Journal of Human Genetics | volume = 80 | issue = 3 | pages = 502–9 | date = March 2007 | pmid = 17273971 | pmc = 1821107 | doi = 10.1086/512017 }}

The population geneticist Sewall Wright developed the fixation index (often abbreviated to F_ST) as a way of measuring genetic differences between populations. This statistic is often used in taxonomy to compare differences between any two given populations by measuring the genetic differences among and between populations for individual genes, or for many genes simultaneously.{{cite web |url=http://raceandgenomics.ssrc.org/Graves/ |title=What We Know and What We Don't Know: Human Genetic Variation and the Social Construction of Race |work=Is Race "Real"? |access-date=2011-01-22 |last=Graves |first=Joseph L. |name-list-style=vanc |date=2006 |publisher=Social Science Research Council |archive-date=3 June 2019 |archive-url=https://web.archive.org/web/20190603030227/http://raceandgenomics.ssrc.org/Graves/ |url-status=dead }} It is often stated that the fixation index for humans is about 0.15. This translates to an estimated 85% of the variation measured in the overall human population is found within individuals of the same population, and about 15% of the variation occurs between populations. These estimates imply that any two individuals from different populations may be more similar to each other than either is to a member of their own group.{{cite journal | vauthors = Keita SO, Kittles RA, Royal CD, Bonney GE, Furbert-Harris P, Dunston GM, Rotimi CN | title = Conceptualizing human variation | journal = Nature Genetics | volume = 36 | issue = 11 Suppl | pages = S17–20 | date = November 2004 | pmid = 15507998 | doi = 10.1038/ng1455 | doi-access = free }}{{cite book |last=Hawks |first=John | name-list-style = vanc |date=2013 |title=Significance of Neandertal and Denisovan Genomes in Human Evolution |journal=Annual Review of Anthropology |publisher=Annual Reviews |volume=42 |issue=1 |pages=433–49 |isbn=978-0-8243-1942-7 |doi=10.1146/annurev-anthro-092412-155548 }}

"The shared evolutionary history of living humans has resulted in a high relatedness among all living people, as indicated for example by the very low fixation index (F_ST) among living human populations." Richard Lewontin, who affirmed these ratios, thus concluded neither "race" nor "subspecies" were appropriate or useful ways to describe human populations.{{cite book |last1=Lewontin |first1=Richard C. | name-list-style = vanc |date=1972 |chapter=The Apportionment of Human Diversity |editor=Theodosius Dobzhansky |editor2=Max K. Hecht |editor3=William C. Steere |title=Evolutionary Biology |volume=6 |pages=381–97 |doi=10.1007/978-1-4684-9063-3_14|isbn=978-1-4684-9065-7 |location=New York |publisher=Appleton–Century–Crofts|s2cid=21095796 }}

Wright himself believed that values >0.25 represent very great genetic variation and that an F_ST of 0.15–0.25 represented great variation. However, about 5% of human variation occurs between populations within continents, therefore F_ST values between continental groups of humans (or races) of as low as 0.1 (or possibly lower) have been found in some studies, suggesting more moderate levels of genetic variation. Graves (1996) has countered that F_ST should not be used as a marker of subspecies status, as the statistic is used to measure the degree of differentiation between populations, although see also Wright (1978).* {{cite book |last=Wright |first=Sewall | name-list-style = vanc |date=1978 |title=Evolution and the Genetics of Populations |volume=4, Variability Within and Among Natural Populations |publisher=Univ. Chicago Press |location=Chicago, Illinois |page=438 }}

Jeffrey Long and Rick Kittles give a long critique of the application of F_ST to human populations in their 2003 paper "Human Genetic Diversity and the Nonexistence of Biological Races". They find that the figure of 85% is misleading because it implies that all human populations contain on average 85% of all genetic diversity. They argue the underlying statistical model incorrectly assumes equal and independent histories of variation for each large human population. A more realistic approach is to understand that some human groups are parental to other groups and that these groups represent paraphyletic groups to their descent groups. For example, under the recent African origin theory the human population in Africa is paraphyletic to all other human groups because it represents the ancestral group from which all non-African populations derive, but more than that, non-African groups only derive from a small non-representative sample of this African population. This means that all non-African groups are more closely related to each other and to some African groups (probably east Africans) than they are to others, and further that the migration out of Africa represented a genetic bottleneck, with much of the diversity that existed in Africa not being carried out of Africa by the emigrating groups. Under this scenario, human populations do not have equal amounts of local variability, but rather diminished amounts of diversity the further from Africa any population lives. Long and Kittles find that rather than 85% of human genetic diversity existing in all human populations, about 100% of human diversity exists in a single African population, whereas only about 70% of human genetic diversity exists in a population derived from New Guinea. Long and Kittles argued that this still produces a global human population that is genetically homogeneous compared to other mammalian populations.{{cite journal | vauthors = Long JC, Kittles RA | title = Human genetic diversity and the nonexistence of biological races | journal = Human Biology | volume = 75 | issue = 4 | pages = 449–71 | date = August 2003 | pmid = 14655871 | doi = 10.1353/hub.2003.0058 | s2cid = 26108602 }}

{{Main|Archaic human admixture with modern humans}}

Anatomically modern humans interbred with Neanderthals during the Middle Paleolithic. In May 2010, the Neanderthal Genome Project presented genetic evidence that interbreeding took place and that a small but significant portion, around 2–4%, of Neanderthal admixture is present in the DNA of modern Eurasians and Oceanians, and nearly absent in sub-Saharan African populations.{{Cite journal|last1=Harris|first1=Kelley|last2=Nielsen|first2=Rasmus|date=June 2016|title=The Genetic Cost of Neanderthal Introgression|journal=Genetics|volume=203|issue=2|pages=881–891|doi=10.1534/genetics.116.186890|issn=0016-6731|pmc=4896200|pmid=27038113}}{{Cite journal|last1=Wall|first1=Jeffrey D.|last2=Yang|first2=Melinda A.|last3=Jay|first3=Flora|last4=Kim|first4=Sung K.|last5=Durand|first5=Eric Y.|last6=Stevison|first6=Laurie S.|last7=Gignoux|first7=Christopher|last8=Woerner|first8=August|last9=Hammer|first9=Michael F.|last10=Slatkin|first10=Montgomery|date=May 2013|title=Higher Levels of Neanderthal Ancestry in East Asians than in Europeans|journal=Genetics|volume=194|issue=1|pages=199–209|doi=10.1534/genetics.112.148213|issn=0016-6731|pmc=3632468|pmid=23410836}}

Between 4% and 6% of the genome of Melanesians (represented by the Papua New Guinean and Bougainville Islander) appears to derive from Denisovans – a previously unknown hominin which is more closely related to Neanderthals than to Sapiens. It was possibly introduced during the early migration of the ancestors of Melanesians into Southeast Asia. This history of interaction suggests that Denisovans once ranged widely over eastern Asia.

{{cite journal | vauthors = Reich D, Green RE, Kircher M, Krause J, Patterson N, Durand EY, Viola B, Briggs AW, Stenzel U, Johnson PL, Maricic T, Good JM, Marques-Bonet T, Alkan C, Fu Q, Mallick S, Li H, Meyer M, Eichler EE, Stoneking M, Richards M, Talamo S, Shunkov MV, Derevianko AP, Hublin JJ, Kelso J, Slatkin M, Pääbo S | display-authors = 6 | title = Genetic history of an archaic hominin group from Denisova Cave in Siberia | journal = Nature | volume = 468 | issue = 7327 | pages = 1053–60 | date = December 2010 | pmid = 21179161 | pmc = 4306417 | doi = 10.1038/nature09710 | bibcode = 2010Natur.468.1053R }}

Thus, Melanesians emerge as one of the most archaic-admixed populations, having Denisovan/Neanderthal-related admixture of ~8%.

In a study published in 2013, Jeffrey Wall from University of California studied whole sequence-genome data and found higher rates of introgression in Asians compared to Europeans.{{cite journal | vauthors = Wall JD, Yang MA, Jay F, Kim SK, Durand EY, Stevison LS, Gignoux C, Woerner A, Hammer MF, Slatkin M | display-authors = 6 | title = Higher levels of neanderthal ancestry in East Asians than in Europeans | journal = Genetics | volume = 194 | issue = 1 | pages = 199–209 | date = May 2013 | pmid = 23410836 | pmc = 3632468 | doi = 10.1534/genetics.112.148213 }} Hammer et al. tested the hypothesis that contemporary African genomes have signatures of gene flow with archaic human ancestors and found evidence of archaic admixture in the genomes of some African groups, suggesting that modest amounts of gene flow were widespread throughout time and space during the evolution of anatomically modern humans.{{cite journal | vauthors = Hammer MF, Woerner AE, Mendez FL, Watkins JC, Wall JD | title = Genetic evidence for archaic admixture in Africa | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 108 | issue = 37 | pages = 15123–8 | date = September 2011 | pmid = 21896735 | pmc = 3174671 | doi = 10.1073/pnas.1109300108 | bibcode = 2011PNAS..10815123H | doi-access = free }}

A study published in 2020 found that the Yoruba and Mende populations of West Africa derive between 2% and 19% of their genome from an as-yet unidentified archaic hominin population that likely diverged before the split of modern humans and the ancestors of Neanderthals and Denisovans,{{cite journal | vauthors = Durvasula A, Sankararaman S | title = Recovering signals of ghost archaic introgression in African populations | journal = Science Advances | volume = 6 | issue = 7 | date = February 2020 | pages = eaax5097 | doi = 10.1126/sciadv.aax5097| pmid = 32095519 | pmc = 7015685 | bibcode = 2020SciA....6.5097D | doi-access = free }} potentially making these groups the most archaic-admixed human populations identified yet.

File:Rosenberg2007.png

File:Human genetic variant counts by region.svg

{{See also|Race (human classification)|Race and genetics}}

New data on human genetic variation has reignited the debate about a possible biological basis for categorization of humans into races. Most of the controversy surrounds the question of how to interpret the genetic data and whether conclusions based on it are sound. Some researchers argue that self-identified race can be used as an indicator of geographic ancestry for certain health risks and medications.

Although the genetic differences among human groups are relatively small, these differences in certain genes such as duffy, ABCC11, SLC24A5, called ancestry-informative markers (AIMs) nevertheless can be used to reliably situate many individuals within broad, geographically based groupings. For example, computer analyses of hundreds of polymorphic loci sampled in globally distributed populations have revealed the existence of genetic clustering that roughly is associated with groups that historically have occupied large continental and subcontinental regions (Rosenberg et al. 2002; Bamshad et al. 2003).

Some commentators have argued that these patterns of variation provide a biological justification for the use of traditional racial categories. They argue that the continental clusterings correspond roughly with the division of human beings into sub-Saharan Africans; Europeans, Western Asians, Central Asians, Southern Asians and Northern Africans; Eastern Asians, Southeast Asians, Polynesians and Native Americans; and other inhabitants of Oceania (Melanesians, Micronesians & Australian Aborigines) (Risch et al. 2002). Other observers disagree, saying that the same data undercut traditional notions of racial groups (King and Motulsky 2002; Calafell 2003; Tishkoff and Kidd 2004). They point out, for example, that major populations considered races or subgroups within races do not necessarily form their own clusters.

Racial categories are also undermined by findings that genetic variants which are limited to one region tend to be rare within that region, variants that are common within a region tend to be shared across the globe, and most differences between individuals, whether they come from the same region or different regions, are due to global variants.{{cite journal |vauthors=Biddanda A, Rice DP, Novembre J| title=A variant-centric perspective on geographic patterns of human allele frequency variation. | journal=eLife | year= 2020 | volume= 9 | issue= | pages= | pmid=33350384 | doi=10.7554/eLife.60107 | pmc=7755386 | doi-access=free }} No genetic variants have been found which are fixed within a continent or major region and found nowhere else.{{cite journal |vauthors=Bergström A, McCarthy SA, Hui R, Almarri MA, Ayub Q, Danecek P | display-authors=etal| title=Insights into human genetic variation and population history from 929 diverse genomes. | journal=Science | year= 2020 | volume= 367 | issue= 6484 | pages= | pmid=32193295 | doi=10.1126/science.aay5012 | pmc=7115999 }}

Furthermore, because human genetic variation is clinal, many individuals affiliate with two or more continental groups. Thus, the genetically based "biogeographical ancestry" assigned to any given person generally will be broadly distributed and will be accompanied by sizable uncertainties (Pfaff et al. 2004).

In many parts of the world, groups have mixed in such a way that many individuals have relatively recent ancestors from widely separated regions. Although genetic analyses of large numbers of loci can produce estimates of the percentage of a person's ancestors coming from various continental populations (Shriver et al. 2003; Bamshad et al. 2004), these estimates may assume a false distinctiveness of the parental populations, since human groups have exchanged mates from local to continental scales throughout history (Cavalli-Sforza et al. 1994; Hoerder 2002). Even with large numbers of markers, information for estimating admixture proportions of individuals or groups is limited, and estimates typically will have wide confidence intervals (Pfaff et al. 2004).

{{Main|Human genetic clustering}}

Genetic data can be used to infer population structure and assign individuals to groups that often correspond with their self-identified geographical ancestry. Jorde and Wooding (2004) argued that "Analysis of many loci now yields reasonably accurate estimates of genetic similarity among individuals, rather than populations. Clustering of individuals is correlated with geographic origin or ancestry." However, identification by geographic origin may quickly break down when considering historical ancestry shared between individuals back in time.{{Cite journal|last1=Albers|first1=Patrick K.|last2=McVean|first2=Gil|date=2018-09-13|title=Dating genomic variants and shared ancestry in population-scale sequencing data|url=https://www.biorxiv.org/content/early/2018/09/13/416610|journal=bioRxiv|volume=18|issue=1|language=en|pages=416610|doi=10.1101/416610|pmid=31951611|pmc=6992231|doi-access=free}}

An analysis of autosomal SNP data from the International HapMap Project (Phase II) and CEPH Human Genome Diversity Panel samples was published in 2009.

The study of 53 populations taken from the HapMap and CEPH data (1138 unrelated individuals) suggested that natural selection may shape the human genome much more slowly than previously thought, with factors such as migration within and among continents more heavily influencing the distribution of genetic variations.{{cite journal | vauthors = Coop G, Pickrell JK, Novembre J, Kudaravalli S, Li J, Absher D, Myers RM, Cavalli-Sforza LL, Feldman MW, Pritchard JK | display-authors = 6 | title = The role of geography in human adaptation | journal = PLOS Genetics | volume = 5 | issue = 6 | pages = e1000500 | date = June 2009 | pmid = 19503611 | pmc = 2685456 | doi = 10.1371/journal.pgen.1000500 | editor1-last = Schierup | editor1-first = Mikkel H. | doi-access = free }}

See also: {{cite news | url = https://www.washingtonpost.com/wp-dyn/content/article/2009/06/21/AR2009062101726_pf.html | title = Among Many Peoples, Little Genomic Variety | newspaper = The Washington Post | date = 22 June 2009 | access-date = 25 June 2009 | first=David | last=Brown | name-list-style = vanc }}.

{{cite web| title= Geography And History Shape Genetic Differences in Humans | url= https://www.sciencedaily.com/releases/2009/06/090605091157.htm | publisher=Science Daily | date= 7 June 2009 | access-date = 25 June 2009}}.

A similar study published in 2010 found strong genome-wide evidence for selection due to changes in ecoregion, diet, and subsistence

particularly in connection with polar ecoregions, with foraging, and with a diet rich in roots and tubers.{{cite journal | vauthors = Hancock AM, Witonsky DB, Ehler E, Alkorta-Aranburu G, Beall C, Gebremedhin A, Sukernik R, Utermann G, Pritchard J, Coop G, Di Rienzo A | display-authors = 6 | title = Colloquium paper: human adaptations to diet, subsistence, and ecoregion are due to subtle shifts in allele frequency | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 107 | pages = 8924–30 | date = May 2010 | issue = Suppl 2 | pmid = 20445095 | pmc = 3024024 | doi = 10.1073/pnas.0914625107 | bibcode = 2010PNAS..107.8924H | doi-access = free }} In a 2016 study, principal component analysis of genome-wide data was capable of recovering previously-known targets for positive selection (without prior definition of populations) as well as a number of new candidate genes.{{cite journal | vauthors = Duforet-Frebourg N, Luu K, Laval G, Bazin E, Blum MG | title = Detecting Genomic Signatures of Natural Selection with Principal Component Analysis: Application to the 1000 Genomes Data | journal = Molecular Biology and Evolution | volume = 33 | issue = 4 | pages = 1082–93 | date = April 2016 | pmid = 26715629 | pmc = 4776707 | doi = 10.1093/molbev/msv334 | arxiv = 1504.04543 }}

Forensic anthropologists can assess the ancestry of skeletal remains by analyzing skeletal morphology as well as using genetic and chemical markers, when possible.{{Cite journal|last1=Cunha|first1=Eugénia|last2=Ubelaker|first2=Douglas H.|date=2019-12-23|title=Evaluation of ancestry from human skeletal remains: a concise review|journal=Forensic Sciences Research|volume=5|issue=2|pages=89–97|doi=10.1080/20961790.2019.1697060|issn=2096-1790|pmc=7476619|pmid=32939424}} While these assessments are never certain, the accuracy of skeletal morphology analyses in determining true ancestry has been estimated at 90%.{{Cite journal|last1=Thomas|first1=Richard M.|last2=Parks|first2=Connie L.|last3=Richard|first3=Adam H.|date=July 2017|title=Accuracy Rates of Ancestry Estimation by Forensic Anthropologists Using Identified Forensic Cases|url=https://pubmed.ncbi.nlm.nih.gov/28133721/|journal=Journal of Forensic Sciences|volume=62|issue=4|pages=971–974|doi=10.1111/1556-4029.13361|issn=1556-4029|pmid=28133721|s2cid=3453064}}

File:Admixture triangle plot.svg showing average admixture of five North American ethnic groups. Individuals that self-identify with each group can be found at many locations on the map, but on average groups tend to cluster differently.]]

{{Main|Gene flow}}

Gene flow between two populations reduces the average genetic distance between the populations, only totally isolated human populations experience no gene flow and most populations have continuous gene flow with other neighboring populations which create the clinal distribution observed for most genetic variation. When gene flow takes place between well-differentiated genetic populations the result is referred to as "genetic admixture".

Admixture mapping is a technique used to study how genetic variants cause differences in disease rates between population.{{cite journal | vauthors = Winkler CA, Nelson GW, Smith MW | title = Admixture mapping comes of age | journal = Annual Review of Genomics and Human Genetics | volume = 11 | pages = 65–89 | year = 2010 | pmid = 20594047 | doi = 10.1146/annurev-genom-082509-141523 | pmc = 7454031 | url = https://zenodo.org/record/1234977 }} Recent admixture populations that trace their ancestry to multiple continents are well suited for identifying genes for traits and diseases that differ in prevalence between parental populations. African-American populations have been the focus of numerous population genetic and admixture mapping studies, including studies of complex genetic traits such as white cell count, body-mass index, prostate cancer and renal disease.{{cite journal | vauthors = Bryc K, Auton A, Nelson MR, Oksenberg JR, Hauser SL, Williams S, Froment A, Bodo JM, Wambebe C, Tishkoff SA, Bustamante CD | display-authors = 6 | title = Genome-wide patterns of population structure and admixture in West Africans and African Americans | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 107 | issue = 2 | pages = 786–91 | date = January 2010 | pmid = 20080753 | pmc = 2818934 | doi = 10.1073/pnas.0909559107 | bibcode = 2010PNAS..107..786B | doi-access = free }}

An analysis of phenotypic and genetic variation including skin color and socio-economic status was carried out in the population of Cape Verde which has a well documented history of contact between Europeans and Africans. The studies showed that pattern of admixture in this population has been sex-biased (involving mostly matings between European men and African women) and there is a significant interaction between socioeconomic status and skin color, independent of ancestry.{{cite journal | vauthors = Beleza S, Campos J, Lopes J, Araújo II, Hoppfer Almada A, Correia e Silva A, Parra EJ, Rocha J | display-authors = 6 | title = The admixture structure and genetic variation of the archipelago of Cape Verde and its implications for admixture mapping studies | journal = PLOS ONE| volume = 7 | issue = 11 | pages = e51103 | year = 2012 | pmid = 23226471 | pmc = 3511383 | doi = 10.1371/journal.pone.0051103 | bibcode = 2012PLoSO...751103B | doi-access = free }} Another study shows an increased risk of graft-versus-host disease complications after transplantation due to genetic variants in human leukocyte antigen (HLA) and non-HLA proteins.{{cite journal | vauthors = Arrieta-Bolaños E, Madrigal JA, Shaw BE | title = Human leukocyte antigen profiles of Latin American populations: differential admixture and its potential impact on hematopoietic stem cell transplantation | journal = Bone Marrow Research | volume = 2012 | pages = 1–13 | year = 2012 | pmid = 23213535 | pmc = 3506882 | doi = 10.1155/2012/136087 | doi-access = free }}

{{See also|Race and health}}

Given that each individual has millions of genetic variants (compared to the reference genome), it is an important question what impact these variants have on human health or gene function. Most genetic variants have only small to moderate effects, if any. Frequently cited examples include hypertension (Douglas et al. 1996), diabetes,{{Cite journal |last1=Gower |first1=Barbara A. |last2=Fernández |first2=José R. |last3=Beasley |first3=T. Mark |last4=Shriver |first4=Mark D. |last5=Goran |first5=Michael I. |date=April 2003 |title=Using genetic admixture to explain racial differences in insulin-related phenotypes |url=https://pubmed.ncbi.nlm.nih.gov/12663479 |journal=Diabetes |volume=52 |issue=4 |pages=1047–1051 |doi=10.2337/diabetes.52.4.1047 |issn=0012-1797 |pmid=12663479}} obesity (Fernandez et al. 2003), and prostate cancer (Platz et al. 2000). However, the role of genetic factors in generating these differences remains uncertain.{{Cite journal |last1=Mountain |first1=Joanna L. |last2=Risch |first2=Neil |date=November 2004 |title=Assessing genetic contributions to phenotypic differences among 'racial' and 'ethnic' groups |url=https://pubmed.ncbi.nlm.nih.gov/15508003 |journal=Nature Genetics |volume=36 |issue=11 Suppl |pages=S48–53 |doi=10.1038/ng1456 |issn=1061-4036 |pmid=15508003}}

The human genome encodes about 20,000 protein-coding genes with about 550 amino acids each.{{Cite web |title=UniProt |url=https://www.uniprot.org/proteomes/UP000005640 |access-date=2025-02-18 |website=www.uniprot.org}} Hence, human proteins span about 11 million amino acids (22 million per diploid genome). The median number of missense mutations in individual human genomes is about 8600, that is, two individuals differ by 1 in about 2600 amino acids or in about 20% of their proteins. The average individual has about 137 (predicted) loss of function mutations, including 71 frameshift and 148 in-frame deletions or insertions. Mutations at 32.2% and 9.5% of all possible genomic positions, respectively, can lead to missense and stop-gained variants (i.e., truncated proteins).{{Cite journal |last1=Sun |first1=Kathie Y. |last2=Bai |first2=Xiaodong |last3=Chen |first3=Siying |last4=Bao |first4=Suying |last5=Zhang |first5=Chuanyi |last6=Kapoor |first6=Manav |last7=Backman |first7=Joshua |last8=Joseph |first8=Tyler |last9=Maxwell |first9=Evan |last10=Mitra |first10=George |last11=Gorovits |first11=Alexander |last12=Mansfield |first12=Adam |last13=Boutkov |first13=Boris |last14=Gokhale |first14=Sujit |last15=Habegger |first15=Lukas |date=July 2024 |title=A deep catalogue of protein-coding variation in 983,578 individuals |journal=Nature |language=en |volume=631 |issue=8021 |pages=583–592 |doi=10.1038/s41586-024-07556-0 |issn=1476-4687 |pmc=11254753 |pmid=38768635|bibcode=2024Natur.631..583S }} In a sample of almost 1 million people, almost 5000 genes were identified that had loss-of-function variants in both alleles of the same individual. That is, if these 5000 genes can tolerate homozygous loss of function mutations, they are unlikely to be essential.

Differences in allele frequencies contribute to group differences in the incidence of some monogenic diseases, and they may contribute to differences in the incidence of some common diseases.{{cite journal | vauthors = Risch N, Burchard E, Ziv E, Tang H | title = Categorization of humans in biomedical research: genes, race and disease | journal = Genome Biology | volume = 3 | issue = 7 | pages = comment2007 | date = July 2002 | pmid = 12184798 | pmc = 139378 | doi = 10.1186/gb-2002-3-7-comment2007 | doi-access = free }} For the monogenic diseases, the frequency of causative alleles usually correlates best with ancestry, whether familial (for example, Ellis–Van Creveld syndrome among the Pennsylvania Amish), ethnic (Tay–Sachs disease among Ashkenazi Jewish populations), or geographical (hemoglobinopathies among people with ancestors who lived in malarial regions). To the extent that ancestry corresponds with racial or ethnic groups or subgroups, the incidence of monogenic diseases can differ between groups categorized by race or ethnicity, and health-care professionals typically take these patterns into account in making diagnoses.{{cite journal | vauthors = Lu YF, Goldstein DB, Angrist M, Cavalleri G | title = Personalized medicine and human genetic diversity | journal = Cold Spring Harbor Perspectives in Medicine | volume = 4 | issue = 9 | pages = a008581 | date = July 2014 | pmid = 25059740 | pmc = 4143101 | doi = 10.1101/cshperspect.a008581 }}

Some other variations on the other hand are beneficial to human, as they prevent certain diseases and increase the chance to adapt to the environment. For example, mutation in CCR5 gene that protects against AIDS. CCR5 gene is absent on the surface of cell due to mutation. Without CCR5 gene on the surface, there is nothing for HIV viruses to grab on and bind into. Therefore, the mutation on CCR5 gene decreases the chance of an individual's risk with AIDS. The mutation in CCR5 is also quite common in certain areas, with more than 14% of the population carry the mutation in Europe and about 6–10% in Asia and North Africa.{{cite journal | vauthors = Limborska SA, Balanovsky OP, Balanovskaya EV, Slominsky PA, Schadrina MI, Livshits LA, Kravchenko SA, Pampuha VM, Khusnutdinova EK, Spitsyn VA | display-authors = 6 | title = Analysis of CCR5Delta32 geographic distribution and its correlation with some climatic and geographic factors | journal = Human Heredity | volume = 53 | issue = 1 | pages = 49–54 | year = 2002 | pmid = 11901272 | doi = 10.1159/000048605 | s2cid = 1538974 }}

File:HIV attachment.gif

Many genetic variants may have aided humans in ancient times but plague us today. For example, genes that allow humans to more efficiently process food also make people susceptible to obesity and diabetes today.{{cite journal | vauthors = Tishkoff SA, Verrelli BC | title = Patterns of human genetic diversity: implications for human evolutionary history and disease | journal = Annual Review of Genomics and Human Genetics | volume = 4 | issue = 1 | pages = 293–340 | year = 2003 | pmid = 14527305 | doi = 10.1146/annurev.genom.4.070802.110226 }}

{{Further|:Category:Human genome projects}}

Human genome projects are scientific endeavors that determine or study the structure of the human genome. The Human Genome Project was a landmark genome project.

There are numerous related projects that deal with genetic variation (or variation in the encoded proteins), e.g. organized by the following organizations:

• HUman Genome Organisation (HUGO) -- organizes activities around human genome sequencing, including variants
• Human Genome Variation Society (HGVS) -- develops nomenclatural standards for human genetic variants
• HGVS Variant Nomenclature Committee (HVNC) -- maps and organizes variant nomenclature

• Archaeogenetics
• Chimera (genetics)
• Genealogical DNA test
• Human evolutionary genetics
• Isolation by distance
• Multiregional hypothesis
• Neurodiversity
• Race and genetics
• Recent single origin hypothesis
• Y-chromosome haplogroups in populations of the world

• 1000 Genomes Project
• African admixture in Europe
• Genetic history of Europe
• Genetic history of indigenous peoples of the Americas
• Genetic history of South Asia
• Genetic history of the British Isles

• Human Variome Project

{{reflist}}

{{refbegin|32em}}

• {{cite journal | title = The use of racial, ethnic, and ancestral categories in human genetics research | journal = American Journal of Human Genetics | volume = 77 | issue = 4 | pages = 519–32 | date = October 2005 | pmid = 16175499 | pmc = 1275602 | doi = 10.1086/491747 | last1 = Race | first1 = Ethnicity }}
• {{cite journal | vauthors = Altmüller J, Palmer LJ, Fischer G, Scherb H, Wjst M | title = Genomewide scans of complex human diseases: true linkage is hard to find | journal = American Journal of Human Genetics | volume = 69 | issue = 5 | pages = 936–50 | date = November 2001 | pmid = 11565063 | pmc = 1274370 | doi = 10.1086/324069 }}
• {{cite journal | vauthors = Aoki K | title = Sexual selection as a cause of human skin colour variation: Darwin's hypothesis revisited | journal = Annals of Human Biology | volume = 29 | issue = 6 | pages = 589–608 | year = 2002 | pmid = 12573076 | doi = 10.1080/0301446021000019144 | s2cid = 22703861 }}
• {{cite journal | vauthors = Bamshad M, Wooding S, Salisbury BA, Stephens JC | title = Deconstructing the relationship between genetics and race | journal = Nature Reviews. Genetics | volume = 5 | issue = 8 | pages = 598–609 | date = August 2004 | pmid = 15266342 | doi = 10.1038/nrg1401 | s2cid = 12378279 }} [https://web.archive.org/web/20051022081358/http://www.xmission.com/~wooding/pdfs/bamshad_race04.zip reprint-zip]
• {{cite journal | vauthors = Bamshad M, Wooding SP | title = Signatures of natural selection in the human genome | journal = Nature Reviews. Genetics | volume = 4 | issue = 2 | pages = 99–111 | date = February 2003 | pmid = 12560807 | doi = 10.1038/nrg999 | s2cid = 13722452 }}
• {{cite journal | vauthors = Cann RL, Stoneking M, Wilson AC | title = Mitochondrial DNA and human evolution | journal = Nature | volume = 325 | issue = 6099 | pages = 31–36 | year = 1987 | pmid = 3025745 | doi = 10.1038/325031a0 | bibcode = 1987Natur.325...31C | s2cid = 4285418 }}
• {{cite journal | vauthors = Cardon LR, Abecasis GR | title = Using haplotype blocks to map human complex trait loci | journal = Trends in Genetics | volume = 19 | issue = 3 | pages = 135–40 | date = March 2003 | pmid = 12615007 | doi = 10.1016/S0168-9525(03)00022-2 | url = http://www.sph.umich.edu/csg/abecasis/publications/pdf/Trends.Genet.vol.19-pp.135.pdf }}
• {{cite journal | vauthors = Cavalli-Sforza LL, Feldman MW | title = The application of molecular genetic approaches to the study of human evolution | journal = Nature Genetics | volume = 33 Suppl | issue = 3s | pages = 266–75 | date = March 2003 | pmid = 12610536 | doi = 10.1038/ng1113 | s2cid = 8314161 }}
• {{cite journal | vauthors = Collins FS | title = What we do and don't know about 'race', 'ethnicity', genetics and health at the dawn of the genome era | journal = Nature Genetics | volume = 36 | issue = 11 Suppl | pages = S13–15 | date = November 2004 | pmid = 15507997 | doi = 10.1038/ng1436 | s2cid = 26968169 | doi-access = free }}
• {{cite journal | vauthors = Collins FS, Green ED, Guttmacher AE, Guyer MS | title = A vision for the future of genomics research | journal = Nature | volume = 422 | issue = 6934 | pages = 835–47 | date = April 2003 | pmid = 12695777 | doi = 10.1038/nature01626 | bibcode = 2003Natur.422..835C | s2cid = 205209730 | doi-access = free }}
• {{cite journal | vauthors = Ebersberger I, Metzler D, Schwarz C, Pääbo S | title = Genomewide comparison of DNA sequences between humans and chimpanzees | journal = American Journal of Human Genetics | volume = 70 | issue = 6 | pages = 1490–97 | date = June 2002 | pmid = 11992255 | pmc = 379137 | doi = 10.1086/340787 }}
• {{cite journal | vauthors = Edwards AW | title = Human genetic diversity: Lewontin's fallacy | journal = BioEssays | volume = 25 | issue = 8 | pages = 798–801 | date = August 2003 | pmid = 12879450 | doi = 10.1002/bies.10315 }}
• {{cite journal | vauthors = Foster MW, Sharp RR | title = Beyond race: towards a whole-genome perspective on human populations and genetic variation | journal = Nature Reviews. Genetics | volume = 5 | issue = 10 | pages = 790–96 | date = October 2004 | pmid = 15510170 | doi = 10.1038/nrg1452 | s2cid = 25764082 }}
• {{cite journal | vauthors = Foster MW, Sharp RR, Freeman WL, Chino M, Bernsten D, Carter TH | title = The role of community review in evaluating the risks of human genetic variation research | journal = American Journal of Human Genetics | volume = 64 | issue = 6 | pages = 1719–27 | date = June 1999 | pmid = 10330360 | pmc = 1377916 | doi = 10.1086/302415 }}
• {{cite journal | vauthors = Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, Liu-Cordero SN, Rotimi C, Adeyemo A, Cooper R, Ward R, Lander ES, Daly MJ, Altshuler D | title = The structure of haplotype blocks in the human genome | journal = Science | volume = 296 | issue = 5576 | pages = 2225–29 | date = June 2002 | pmid = 12029063 | doi = 10.1126/science.1069424 | bibcode = 2002Sci...296.2225G | s2cid = 10069634 | doi-access = free }}
• {{cite journal | vauthors = Harding RM, Healy E, Ray AJ, Ellis NS, Flanagan N, Todd C, Dixon C, Sajantila A, Jackson IJ, Birch-Machin MA, Rees JL | title = Evidence for variable selective pressures at MC1R | journal = American Journal of Human Genetics | volume = 66 | issue = 4 | pages = 1351–61 | date = April 2000 | pmid = 10733465 | pmc = 1288200 | doi = 10.1086/302863 }}
• {{cite journal | vauthors = Ingman M, Kaessmann H, Pääbo S, Gyllensten U | title = Mitochondrial genome variation and the origin of modern humans | journal = Nature | volume = 408 | issue = 6813 | pages = 708–13 | date = December 2000 | pmid = 11130070 | doi = 10.1038/35047064 | bibcode = 2000Natur.408..708I | s2cid = 52850476 }}
• {{cite journal | author = The International Hapmap Consortium | title = The International HapMap Project | journal = Nature | volume = 426 | issue = 6968 | pages = 789–96 | date = December 2003 | pmid = 14685227 | doi = 10.1038/nature02168 | hdl = 2027.42/62838 | bibcode = 2003Natur.426..789G | s2cid = 4387110 | hdl-access = free }}
• {{cite journal | author = The International Hapmap Consortium | title = Integrating ethics and science in the International HapMap Project | journal = Nature Reviews. Genetics | volume = 5 | issue = 6 | pages = 467–75 | date = June 2004 | pmid = 15153999 | pmc = 2271136 | doi = 10.1038/nrg1351 }}
• {{cite journal | vauthors = Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, Devon K, Dewar K, Doyle M, FitzHugh W, Funke R, Gage D, Harris K, Heaford A, Howland J, Kann L, Lehoczky J, LeVine R, McEwan P, McKernan K, Meldrim J, Mesirov JP, Miranda C, Morris W, Naylor J, Raymond C, Rosetti M, Santos R, Sheridan A, Sougnez C, Stange-Thomann Y, Stojanovic N, Subramanian A, Wyman D, Rogers J, Sulston J, Ainscough R, Beck S, Bentley D, Burton J, Clee C, Carter N, Coulson A, Deadman R, Deloukas P, Dunham A, Dunham I, Durbin R, French L, Grafham D, Gregory S, Hubbard T, Humphray S, Hunt A, Jones M, Lloyd C, McMurray A, Matthews L, Mercer S, Milne S, Mullikin JC, Mungall A, Plumb R, Ross M, Shownkeen R, Sims S, Waterston RH, Wilson RK, Hillier LW, McPherson JD, Marra MA, Mardis ER, Fulton LA, Chinwalla AT, Pepin KH, Gish WR, Chissoe SL, Wendl MC, Delehaunty KD, Miner TL, Delehaunty A, Kramer JB, Cook LL, Fulton RS, Johnson DL, Minx PJ, Clifton SW, Hawkins T, Branscomb E, Predki P, Richardson P, Wenning S, Slezak T, Doggett N, Cheng JF, Olsen A, Lucas S, Elkin C, Uberbacher E, Frazier M, Gibbs RA, Muzny DM, Scherer SE, Bouck JB, Sodergren EJ, Worley KC, Rives CM, Gorrell JH, Metzker ML, Naylor SL, Kucherlapati RS, Nelson DL, Weinstock GM, Sakaki Y, Fujiyama A, Hattori M, Yada T, Toyoda A, Itoh T, Kawagoe C, Watanabe H, Totoki Y, Taylor T, Weissenbach J, Heilig R, Saurin W, Artiguenave F, Brottier P, Bruls T, Pelletier E, Robert C, Wincker P, Smith DR, Doucette-Stamm L, Rubenfield M, Weinstock K, Lee HM, Dubois J, Rosenthal A, Platzer M, Nyakatura G, Taudien S, Rump A, Yang H, Yu J, Wang J, Huang G, Gu J, Hood L, Rowen L, Madan A, Qin S, Davis RW, Federspiel NA, Abola AP, Proctor MJ, Myers RM, Schmutz J, Dickson M, Grimwood J, Cox DR, Olson MV, Kaul R, Raymond C, Shimizu N, Kawasaki K, Minoshima S, Evans GA, Athanasiou M, Schultz R, Roe BA, Chen F, Pan H, Ramser J, Lehrach H, Reinhardt R, McCombie WR, de la Bastide M, Dedhia N, Blöcker H, Hornischer K, Nordsiek G, Agarwala R, Aravind L, Bailey JA, Bateman A, Batzoglou S, Birney E, Bork P, Brown DG, Burge CB, Cerutti L, Chen HC, Church D, Clamp M, Copley RR, Doerks T, Eddy SR, Eichler EE, Furey TS, Galagan J, Gilbert JG, Harmon C, Hayashizaki Y, Haussler D, Hermjakob H, Hokamp K, Jang W, Johnson LS, Jones TA, Kasif S, Kaspryzk A, Kennedy S, Kent WJ, Kitts P, Koonin EV, Korf I, Kulp D, Lancet D, Lowe TM, McLysaght A, Mikkelsen T, Moran JV, Mulder N, Pollara VJ, Ponting CP, Schuler G, Schultz J, Slater G, Smit AF, Stupka E, Szustakowki J, Thierry-Mieg D, Thierry-Mieg J, Wagner L, Wallis J, Wheeler R, Williams A, Wolf YI, Wolfe KH, Yang SP, Yeh RF, Collins F, Guyer MS, Peterson J, Felsenfeld A, Wetterstrand KA, Patrinos A, Morgan MJ, de Jong P, Catanese JJ, Osoegawa K, Shizuya H, Choi S, Chen YJ, Szustakowki J | display-authors = 6 | title = Initial sequencing and analysis of the human genome | journal = Nature | volume = 409 | issue = 6822 | pages = 860–921 | date = February 2001 | pmid = 11237011 | doi = 10.1038/35057062 | bibcode = 2001Natur.409..860L | doi-access = free | hdl = 2027.42/62798 | hdl-access = free }}
• {{cite journal | vauthors = Jorde LB, Bamshad M, Rogers AR | title = Using mitochondrial and nuclear DNA markers to reconstruct human evolution | journal = BioEssays | volume = 20 | issue = 2 | pages = 126–36 | date = February 1998 | pmid = 9631658 | doi = 10.1002/(SICI)1521-1878(199802)20:2<126::AID-BIES5>3.0.CO;2-R | s2cid = 17203268 | url = http://jorde-lab.genetics.utah.edu/elibrary/Jorde_1998.pdf | access-date = 28 October 2007 | archive-url = https://web.archive.org/web/20071128030242/http://jorde-lab.genetics.utah.edu/elibrary/Jorde_1998.pdf | archive-date = 28 November 2007 | url-status = dead }}
• {{cite journal | vauthors = Jorde LB, Watkins WS, Bamshad MJ, Dixon ME, Ricker CE, Seielstad MT, Batzer MA | title = The distribution of human genetic diversity: a comparison of mitochondrial, autosomal, and Y-chromosome data | journal = American Journal of Human Genetics | volume = 66 | issue = 3 | pages = 979–88 | date = March 2000 | pmid = 10712212 | pmc = 1288178 | doi = 10.1086/302825 }}
• {{cite journal | vauthors = Jorde LB, Watkins WS, Kere J, Nyman D, Eriksson AW | title = Gene mapping in isolated populations: new roles for old friends? | journal = Human Heredity | volume = 50 | issue = 1 | pages = 57–65 | year = 2000 | pmid = 10545758 | doi = 10.1159/000022891 | s2cid = 26960216 }}
• {{cite journal | vauthors = Kaessmann H, Heissig F, von Haeseler A, Pääbo S | title = DNA sequence variation in a non-coding region of low recombination on the human X chromosome | journal = Nature Genetics | volume = 22 | issue = 1 | pages = 78–81 | date = May 1999 | pmid = 10319866 | doi = 10.1038/8785 | s2cid = 9153915 }}
• {{cite journal | vauthors = Kaessmann H, Wiebe V, Weiss G, Pääbo S | title = Great ape DNA sequences reveal a reduced diversity and an expansion in humans | journal = Nature Genetics | volume = 27 | issue = 2 | pages = 155–56 | date = February 2001 | pmid = 11175781 | doi = 10.1038/84773 | s2cid = 19384784 }}
• {{cite journal

| vauthors = Keita SO, Kittles RA

|year=1997

|title=The Persistence of Racial Thinking and the Myth of Racial Divergence

|journal=American Anthropologist

|volume=99 |issue=3 |pages=534–44

|doi=10.1525/aa.1997.99.3.534

}}

• {{cite book

|title=Human Biodiversity: Genes, Race, and History

|publisher=Aldine Transaction

|year=1995

|isbn=978-0-202-02033-4

|vauthors=Marks J

|url-access=registration

|url=https://archive.org/details/humanbiodiversit0000mark

}}

• {{cite journal | vauthors = Mountain JL, Risch N | title = Assessing genetic contributions to phenotypic differences among 'racial' and 'ethnic' groups | journal = Nature Genetics | volume = 36 | issue = 11 Suppl | pages = S48–53 | date = November 2004 | pmid = 15508003 | doi = 10.1038/ng1456 | doi-access = free }}
• {{cite journal | vauthors = Pääbo S | title = The mosaic that is our genome | journal = Nature | volume = 421 | issue = 6921 | pages = 409–12 | date = January 2003 | pmid = 12540910 | doi = 10.1038/nature01400 | bibcode = 2003Natur.421..409P | doi-access = free }}
• {{cite journal | vauthors = Ramachandran S, Deshpande O, Roseman CC, Rosenberg NA, Feldman MW, Cavalli-Sforza LL | title = Support from the relationship of genetic and geographic distance in human populations for a serial founder effect originating in Africa | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 102 | issue = 44 | pages = 15942–47 | date = November 2005 | pmid = 16243969 | pmc = 1276087 | doi = 10.1073/pnas.0507611102 | bibcode = 2005PNAS..10215942R | doi-access = free }}
• {{cite journal | vauthors = Relethford JH | title = Apportionment of global human genetic diversity based on craniometrics and skin color | journal = American Journal of Physical Anthropology | volume = 118 | issue = 4 | pages = 393–98 | date = August 2002 | pmid = 12124919 | doi = 10.1002/ajpa.10079 | citeseerx = 10.1.1.473.5972 | s2cid = 8717358 }}
• {{cite journal | vauthors = Sankar P, Cho MK | title = Genetics. Toward a new vocabulary of human genetic variation | journal = Science | volume = 298 | issue = 5597 | pages = 1337–38 | date = November 2002 | pmid = 12434037 | pmc = 2271140 | doi = 10.1126/science.1074447 }}
• {{cite journal | vauthors = Sankar P, Cho MK, Condit CM, Hunt LM, Koenig B, Marshall P, Lee SS, Spicer P | title = Genetic research and health disparities | journal = JAMA | volume = 291 | issue = 24 | pages = 2985–89 | date = June 2004 | pmid = 15213210 | pmc = 2271142 | doi = 10.1001/jama.291.24.2985 }}
• {{cite journal | vauthors = Serre D, Pääbo S | title = Evidence for gradients of human genetic diversity within and among continents | journal = Genome Research | volume = 14 | issue = 9 | pages = 1679–85 | date = September 2004 | pmid = 15342553 | pmc = 515312 | doi = 10.1101/gr.2529604 }}
• {{cite journal

|year=1998

|title=Human Races: A Genetic and Evolutionary Perspective

|journal=American Anthropologist

|volume=100|issue=3 |pages=632–50

|doi=10.1525/aa.1998.100.3.632

| vauthors = Templeton AR

|doi-access=free

}}

• {{cite journal

|year=1998

|title=Coming to Terms with Human Variation

|journal=Annual Review of Anthropology

|volume=27|pages=273–300

|doi=10.1146/annurev.anthro.27.1.273

| vauthors = Weiss KM

}}

• {{cite journal | vauthors = Weiss KM, Terwilliger JD | title = How many diseases does it take to map a gene with SNPs? | journal = Nature Genetics | volume = 26 | issue = 2 | pages = 151–57 | date = October 2000 | pmid = 11017069 | doi = 10.1038/79866 | s2cid = 685795 }}
• {{cite journal | vauthors = Yu N, Jensen-Seaman MI, Chemnick L, Kidd JR, Deinard AS, Ryder O, Kidd KK, Li WH | title = Low nucleotide diversity in chimpanzees and bonobos | journal = Genetics | volume = 164 | issue = 4 | pages = 1511–18 | date = August 2003 | doi = 10.1093/genetics/164.4.1511 | pmid = 12930756 | pmc = 1462640 }}
• {{cite journal | vauthors = Zietkiewicz E, Yotova V, Gehl D, Wambach T, Arrieta I, Batzer M, Cole DE, Hechtman P, Kaplan F, Modiano D, Moisan JP, Michalski R, Labuda D | title = Haplotypes in the dystrophin DNA segment point to a mosaic origin of modern human diversity | journal = American Journal of Human Genetics | volume = 73 | issue = 5 | pages = 994–1015 | date = November 2003 | pmid = 14513410 | pmc = 1180505 | doi = 10.1086/378777 }}
• {{cite journal | vauthors = Pennisi E | author-link = Elizabeth Pennisi | title = Breakthrough of the year. Human genetic variation | journal = Science | volume = 318 | issue = 5858 | pages = 1842–43 | date = December 2007 | pmid = 18096770 | doi = 10.1126/science.318.5858.1842 | doi-access = free }}
• {{cite book | vauthors = Ramachandran S, Tang H, Gutenkunst RN, Bustamante CD |year=2010 |chapter=Genetics and Genomics of Human Population Structure | veditors = Speicher MR, Antonarakis SE, Motulsky AG |title=Vogel and Motulsky's Human Genetics: Problems and Approaches |edition=4th |publisher=Springer |isbn=978-3-540-37653-8 }}

{{refend}}

{{Commons category|Human genetic diversity}}

• [http://www.hgvs.org/ Human Genome Variation Society]

{{Human group differences}}

{{Human genetics}}

{{Population genetics}}

{{Personal genomics}}

{{Breakthrough of the Year}}

{{DEFAULTSORT:Human Genetic Variation}}

Category:Human population genetics

Category:Biological anthropology

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