\n\n \n\n \n\n \n \n\n \n\n \n \n\n \n\n \n

\n generated by\n \n $\"bibbase.org\"\n$ \n \n

\n \n\n

\n\n

\n \n Group by\n \n \n
- \n Year\n
- \n Author\n
- \n Type\n
- \n Keyword\n
- \n Downloads\n
\n
\n \n \n \n \n
- \n \n Expand/Collapse All\n \n
- \n \n Download BibTeX\n \n
- \n \n RSS Feed\n \n
\n

\n\n\n

\n\n Excellent! Next you can\n create a new website with this list, or\n embed it in an existing web page by copying & pasting\n any of the following snippets.\n\n

\n JavaScript\n (easiest)\n

\n            <script src=\"https://bibbase.org/show?bib=https%3A%2F%2Fgithub.com%2Fdjcotter%2Fdjcotter.github.io%2Fraw%2Fmaster%2Freferences.bib&jsonp=1&theme=dividers&owner=cotter&hidemenu=1&nocache=1&jsonp=1\"></script>\n

\n\n PHP\n

\n            <?php\n            $contents = file_get_contents(\"https://bibbase.org/show?bib=https%3A%2F%2Fgithub.com%2Fdjcotter%2Fdjcotter.github.io%2Fraw%2Fmaster%2Freferences.bib&jsonp=1&theme=dividers&owner=cotter&hidemenu=1&nocache=1\");\n            print_r($contents);\n            ?>\n

\n\n iFrame\n (not recommended)\n

\n            <iframe src=\"https://bibbase.org/show?bib=https%3A%2F%2Fgithub.com%2Fdjcotter%2Fdjcotter.github.io%2Fraw%2Fmaster%2Freferences.bib&jsonp=1&theme=dividers&owner=cotter&hidemenu=1&nocache=1\"></iframe>\n

\n\n

\n For more details see the documention.\n

\n\n

\n\n This is a preview! To use this list on your own web site\n or create a new web site from it,\n create a free account. The file will be added\n and you will be able to edit it in the File Manager.\n We will show you instructions once you've created your account.\n

\n\n

To the site owner:

\n\n

Action required! Mendeley is changing its\n API. In order to keep using Mendeley with BibBase past April\n 14th, you need to:\n

renew the authorization for BibBase on Mendeley, and
update the BibBase URL\n in your page the same way you did when you initially set up\n this page.\n

\n\n

\n \n \n Fix it now\n

\n\n

\n\n\n

\n \n \n

\n \n 2024\n \n \n (1)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Modeling the effects of consanguinity on autosomal and X-chromosomal runs of homozygosity and identity-by-descent sharing.\n \n \n \n \n\n\n \n Cotter, D. J; Severson, A. L; Kang, J. T L; Godrej, H. N; Carmi, S.; and Rosenberg, N. A\n\n\n \n\n\n\n G3 Genes|Genomes|Genetics, 14(2): jkad264. February 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Modeling$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{cotter_roh_ibd,\n    author = {Cotter, Daniel J and Severson, Alissa L and Kang, Jonathan T L and Godrej, Hormazd N and Carmi, Shai and Rosenberg, Noah A},\n    title = {Modeling the effects of consanguinity on autosomal and {X}-chromosomal runs of homozygosity and identity-by-descent sharing},\n    journal = {G3 Genes|Genomes|Genetics},\n    year = {2024},\n    month = feb,\n    abstract = {Runs of homozygosity (ROH) and identity-by-descent (IBD) sharing can be studied in diploid coalescent models by noting that ROH and IBD-sharing at a genomic site are predicted to be inversely related to coalescence times—which in turn can be mathematically obtained in terms of parameters describing consanguinity rates. Comparing autosomal and X-chromosomal coalescent models, we consider ROH and IBD-sharing in relation to consanguinity that proceeds via multiple forms of first-cousin mating. We predict that across populations with different levels of consanguinity, (1) in a manner that is qualitatively parallel to the increase of autosomal IBD-sharing with autosomal ROH, X-chromosomal IBD-sharing increases with X-chromosomal ROH, owing to the dependence of both quantities on consanguinity levels; (2) even in the absence of consanguinity, X-chromosomal ROH and IBD-sharing levels exceed corresponding values for the autosomes, owing to the smaller population size and lower coalescence time for the X chromosome than for autosomes; (3) with matrilateral consanguinity, the relative increase in ROH and IBD-sharing on the X chromosome compared to the autosomes is greater than in the absence of consanguinity. Examining genome-wide SNPs in human populations for which consanguinity levels have been estimated, we find that autosomal and X-chromosomal ROH and IBD-sharing levels generally accord with the predictions. We find that each 1\\\\% increase in autosomal ROH is associated with an increase of 2.1\\\\% in X-chromosomal ROH, and each 1\\\\% increase in autosomal IBD-sharing is associated with an increase of 1.6\\\\% in X-chromosomal IBD-sharing. For each calculation, particularly for ROH, the estimate is reasonably close to the increase of 2\\\\% predicted by the population-size difference between autosomes and X chromosomes. The results support the utility of coalescent models for understanding patterns of genomic sharing and their dependence on sex-biased processes.},\n    doi = {10.1093/g3journal/jkad264},\n    url = {https://doi.org/10.1093/g3journal/jkad264},\n    eprint = {https://academic.oup.com/g3journal/advance-article-pdf/doi/10.1093/g3journal/jkad264/53477402/jkad264.pdf},\n    volume = {14},\n    number = {2},\n    pages = {jkad264}\n}\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2023\n \n \n (3)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Increasing equity in science requires better ethics training: a course by trainees, for trainees.\n \n \n \n \n\n\n \n Patel, R. A; Ungar, R. A; Pyke, A. L; Adimoelja, A.; Chakraborty, M.; Cotter, D. J; Freund, M.; Goddard, P.; Gomez-Stafford, J.; Greenwald, E.; Higgs, E.; Hunter, N.; MacKenzie, T. M. G.; Narain, A.; and Martschenko, D. O.\n\n\n \n\n\n\n bioRxiv. November 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Increasing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{Patel2023,\n  doi = {10.1101/2023.11.03.565577},\n  url = {https://doi.org/10.1101/2023.11.03.565577},\n  year = {2023},\n  month = nov,\n  journal = {bioRxiv},\n  author = {Roshni A Patel and Rachel A Ungar and Alanna L Pyke and Alvina Adimoelja and Meenakshi Chakraborty and Daniel J Cotter and Malika Freund and Pag{\\'{e}} Goddard and Justin Gomez-Stafford and Emily Greenwald and Emily Higgs and Naiomi Hunter and Tim M. G. MacKenzie and Anjali Narain and Daphne Oluwaseun Martschenko},\n  title = {Increasing equity in science requires better ethics training: a course by trainees, for trainees},\n  abstract = {Despite the profound impacts of scientific research, few scientists have received the necessary training to productively discuss the ethical and societal implications of their work. To address this critical gap, we - a group of predominantly human genetics trainees - developed a course on genetics, ethics, and society. We intend for this course to serve as a template for other institutions and scientific disciplines. Our curriculum positions human genetics within its historical and societal context and encourages students to evaluate how societal norms and structures impact the conduct of scientific research. We demonstrate the utility of this course via surveys of enrolled students and provide resources and strategies for others hoping to teach a similar course. We conclude by arguing that if we are to work towards rectifying the inequities and injustices produced by our field, we must first learn to view our own research as impacting and being impacted by society.}\n}\n\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Genomic and demographic processes differentially influence genetic variation across the human X chromosome.\n \n \n \n \n\n\n \n Cotter, D. J.; Webster, T. H.; and Wilson, M. A.\n\n\n \n\n\n\n PLOS ONE, 18(11): e0287609. November 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Genomic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{Cotter_genomic_2023,\n doi = {10.1371/journal.pone.0287609},\n author = {Cotter, Daniel J. and Webster, Timothy H. and Wilson, Melissa A.},\n journal = {PLOS ONE},\n publisher = {Public Library of Science},\n title = {Genomic and demographic processes differentially influence genetic variation across the human X chromosome},\n year = {2023},\n month = nov,\n volume = {18},\n url = {https://doi.org/10.1371/journal.pone.0287609},\n pages = {e0287609},\n abstract = {Many forces influence genetic variation across the genome including mutation, recombination, selection, and demography. Increased mutation and recombination both lead to increases in genetic diversity in a region-specific manner, while complex demographic patterns shape patterns of diversity on a more global scale. While these processes act across the entire genome, the X chromosome is particularly interesting because it contains several distinct regions that are subject to different combinations and strengths of these forces: the pseudoautosomal regions (PARs) and the X-transposed region (XTR). The X chromosome thus can serve as a unique model for studying how genetic and demographic forces act in different contexts to shape patterns of observed variation. We therefore sought to explore diversity, divergence, and linkage disequilibrium in each region of the X chromosome using genomic data from 26 human populations. Across populations, we find that both diversity and substitution rate are consistently elevated in PAR1 and the XTR compared to the rest of the X chromosome. In contrast, linkage disequilibrium is lowest in PAR1, consistent with the high recombination rate in this region, and highest in the region of the X chromosome that does not recombine in males. However, linkage disequilibrium in the XTR is intermediate between PAR1 and the autosomes, and much lower than the non-recombining X. Finally, in addition to these global patterns, we also observed variation in ratios of X versus autosomal diversity consistent with population-specific evolutionary history as well. While our results were generally consistent with previous work, two unexpected observations emerged. First, our results suggest that the XTR does not behave like the rest of the recombining X and may need to be evaluated separately in future studies. Second, the different regions of the X chromosome appear to exhibit unique patterns of linked selection across different human populations. Together, our results highlight profound regional differences across the X chromosome, simultaneously making it an ideal system for exploring the action of evolutionary forces as well as necessitating its careful consideration and treatment in genomic analyses.},\n number = {11},\n}\n\n

\n\n\n

\n Many forces influence genetic variation across the genome including mutation, recombination, selection, and demography. Increased mutation and recombination both lead to increases in genetic diversity in a region-specific manner, while complex demographic patterns shape patterns of diversity on a more global scale. While these processes act across the entire genome, the X chromosome is particularly interesting because it contains several distinct regions that are subject to different combinations and strengths of these forces: the pseudoautosomal regions (PARs) and the X-transposed region (XTR). The X chromosome thus can serve as a unique model for studying how genetic and demographic forces act in different contexts to shape patterns of observed variation. We therefore sought to explore diversity, divergence, and linkage disequilibrium in each region of the X chromosome using genomic data from 26 human populations. Across populations, we find that both diversity and substitution rate are consistently elevated in PAR1 and the XTR compared to the rest of the X chromosome. In contrast, linkage disequilibrium is lowest in PAR1, consistent with the high recombination rate in this region, and highest in the region of the X chromosome that does not recombine in males. However, linkage disequilibrium in the XTR is intermediate between PAR1 and the autosomes, and much lower than the non-recombining X. Finally, in addition to these global patterns, we also observed variation in ratios of X versus autosomal diversity consistent with population-specific evolutionary history as well. While our results were generally consistent with previous work, two unexpected observations emerged. First, our results suggest that the XTR does not behave like the rest of the recombining X and may need to be evaluated separately in future studies. Second, the different regions of the X chromosome appear to exhibit unique patterns of linked selection across different human populations. Together, our results highlight profound regional differences across the X chromosome, simultaneously making it an ideal system for exploring the action of evolutionary forces as well as necessitating its careful consideration and treatment in genomic analyses.\n

\n\n\n

\n \n\n \n \n \n \n \n \n A rarefaction approach for measuring population differences in rare and common variation.\n \n \n \n \n\n\n \n Cotter, D. J; Hofgard, E. F; Novembre, J.; Szpiech, Z. A; and Rosenberg, N. A\n\n\n \n\n\n\n Genetics, 224(2): iyad070. April 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{Cotter2023,\n    author = {Cotter, Daniel J and Hofgard, Elyssa F and Novembre, John and Szpiech, Zachary A and Rosenberg, Noah A},\n    title = "{A rarefaction approach for measuring population differences in rare and common variation}",\n    journal = {Genetics},\n    volume = {224},\n    number = {2},\n    year = {2023},\n    month = apr,\n    abstract = "{In studying allele-frequency variation across populations, it is often convenient to classify an allelic type as “rare,” with nonzero frequency less than or equal to a specified threshold, “common,” with a frequency above the threshold, or entirely unobserved in a population. When sample sizes differ across populations, however, especially if the threshold separating “rare” and “common” corresponds to a small number of observed copies of an allelic type, discreteness effects can lead a sample from one population to possess substantially more rare allelic types than a sample from another population, even if the two populations have extremely similar underlying allele-frequency distributions across loci. We introduce a rarefaction-based sample-size correction for use in comparing rare and common variation across multiple populations whose sample sizes potentially differ. We use our approach to examine rare and common variation in worldwide human populations, finding that the sample-size correction introduces subtle differences relative to analyses that use the full available sample sizes. We introduce several ways in which the rarefaction approach can be applied: we explore the dependence of allele classifications on subsample sizes, we permit more than two classes of allelic types of nonzero frequency, and we analyze rare and common variation in sliding windows along the genome. The results can assist in clarifying similarities and differences in allele-frequency patterns across populations.}",\n    issn = {1943-2631},\n    doi = {10.1093/genetics/iyad070},\n    url = {https://doi.org/10.1093/genetics/iyad070},\n    pages = {iyad070}\n}\n\n

\n\n\n\n\n\n

\n\n

\n \n 2022\n \n \n (1)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Limiting distribution of X-chromosomal coalescence times under first-cousin consanguineous mating.\n \n \n \n \n\n\n \n Cotter, D. J.; Severson, A. L.; Carmi, S.; and Rosenberg, N. A.\n\n\n \n\n\n\n Theoretical Population Biology, 147: 1–15. October 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Limiting$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{cotter_limiting_2022,\n\ttitle = {Limiting distribution of {X}-chromosomal coalescence times under first-cousin consanguineous mating},\n\tvolume = {147},\n\tissn = {00405809},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0040580922000508},\n\tdoi = {10.1016/j.tpb.2022.07.002},\n\tabstract = {By providing additional opportunities for coalescence within families, the presence of consanguineous unions in a population reduces coalescence times relative to non-consanguineous populations. First-cousin consanguinity can take one of six forms differing in the configuration of sexes in the pedigree of the male and female cousins who join in a consanguineous union: patrilateral parallel, patrilateral cross, matrilateral parallel, matrilateral cross, bilateral parallel, and bilateral cross. Considering populations with each of the six types of first-cousin consanguinity individually and a population with a mixture of the four unilateral types, we examine coalescent models of consanguinity. We previously computed, for first-cousin consanguinity models, the mean coalescence time for X-chromosomal loci and the limiting distribution of coalescence times for autosomal loci. Here, we use the separation-of-time-scales approach to obtain the limiting distribution of coalescence times for X-chromosomal loci. This limiting distribution has an instantaneous coalescence probability that depends on the probability that a union is consanguineous; lineages that do not coalesce instantaneously coalesce according to an exponential distribution. We study the effects on the coalescence time distribution of the type of first-cousin consanguinity, showing that patrilateral-parallel and patrilateral-cross consanguinity have no effect on X-chromosomal coalescence time distributions and that matrilateral-parallel consanguinity decreases coalescence times to a greater extent than does matrilateral-cross consanguinity.},\n\tlanguage = {en},\n\turldate = {2022-08-29},\n\tjournal = {Theoretical Population Biology},\n\tauthor = {Cotter, Daniel J. and Severson, Alissa L. and Carmi, Shai and Rosenberg, Noah A.},\n\tmonth = oct,\n\tyear = {2022},\n\tpages = {1--15},\n}\n\n

\n\n\n\n\n\n

\n\n

\n \n 2021\n \n \n (1)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n The effect of consanguinity on coalescence times on the X chromosome.\n \n \n \n \n\n\n \n Cotter, D. J.; Severson, A. L.; and Rosenberg, N. A.\n\n\n \n\n\n\n Theoretical Population Biology, 140: 32–43. August 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{cotter_effect_2021,\n\ttitle = {The effect of consanguinity on coalescence times on the {X} chromosome},\n\tvolume = {140},\n\tissn = {0040-5809},\n\turl = {https://www.sciencedirect.com/science/article/pii/S0040580921000290},\n\tdoi = {10.1016/j.tpb.2021.03.004},\n\tabstract = {Consanguineous unions increase the frequency at which identical genomic segments are inherited along separate paths of descent, decreasing coalescence times for pairs of alleles drawn from an individual who is the offspring of a consanguineous pair. For an autosomal locus, it has recently been shown that the mean time to the most recent common ancestor (TMRCA) for two alleles in the same individual and the mean TMRCA for two alleles in two separate individuals both decrease with increasing consanguinity in a population. Here, we extend this analysis to the X chromosome, considering X-chromosomal coalescence times under a coalescent model with diploid, male–female mating pairs. We examine four possible first-cousin mating schemes that are equivalent in their effects on autosomes, but that have differing effects on the X chromosome: patrilateral-parallel, patrilateral-cross, matrilateral-parallel, and matrilateral-cross. In each mating model, we calculate mean TMRCA for X-chromosomal alleles sampled either within or between individuals. We describe a consanguinity effect on X-chromosomal TMRCA that differs from the autosomal pattern under matrilateral but not under patrilateral first-cousin mating. For matrilateral first cousins, the effect of consanguinity in reducing TMRCA is stronger on the X chromosome than on the autosomes, with an increased effect of parallel-cousin mating compared to cross-cousin mating. The theoretical computations support the utility of the model in understanding patterns of genomic sharing on the X chromosome.},\n\tlanguage = {en},\n\turldate = {2021-09-07},\n\tjournal = {Theoretical Population Biology},\n\tauthor = {Cotter, Daniel J. and Severson, Alissa L. and Rosenberg, Noah A.},\n\tmonth = aug,\n\tyear = {2021},\n\tkeywords = {Coalescent theory, Consanguinity, Identity by descent, Runs of homozygosity, X chromosome},\n\tpages = {32--43},\n}\n\n

\n\n\n\n\n\n

\n\n

\n \n 2020\n \n \n (1)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n The impact of sex on gene expression across human tissues.\n \n \n \n \n\n\n \n Oliva, M.; Muñoz-Aguirre, M.; Kim-Hellmuth, S.; Wucher, V.; Gewirtz, A. D. H.; Cotter, D. J.; Parsana, P.; Kasela, S.; Balliu, B.; Viñuela, A.; Castel, S. E.; Mohammadi, P.; Aguet, F.; Zou, Y.; Khramtsova, E. A.; Skol, A. D.; Garrido-Martín, D.; Reverter, F.; Brown, A.; Evans, P.; Gamazon, E. R.; Payne, A.; Bonazzola, R.; Barbeira, A. N.; Hamel, A. R.; Martinez-Perez, A.; Soria, J. M.; GTEx Consortium; Pierce, B. L.; Stephens, M.; Eskin, E.; Dermitzakis, E. T.; Segrè, A. V.; Im, H. K.; Engelhardt, B. E.; Ardlie, K. G.; Montgomery, S. B.; Battle, A. J.; Lappalainen, T.; Guigó, R.; and Stranger, B. E.\n\n\n \n\n\n\n Science, 369(6509). September 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{oliva_impact_2020,\n\ttitle = {The impact of sex on gene expression across human tissues},\n\tvolume = {369},\n\tissn = {0036-8075, 1095-9203},\n\turl = {http://science.sciencemag.org/content/369/6509/eaba3066},\n\tdoi = {10.1126/science.aba3066},\n\tabstract = {Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37\\% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.},\n\tlanguage = {en},\n\tnumber = {6509},\n\turldate = {2020-09-10},\n\tjournal = {Science},\n\tauthor = {Oliva, Meritxell and Muñoz-Aguirre, Manuel and Kim-Hellmuth, Sarah and Wucher, Valentin and Gewirtz, Ariel D. H. and Cotter, Daniel J. and Parsana, Princy and Kasela, Silva and Balliu, Brunilda and Viñuela, Ana and Castel, Stephane E. and Mohammadi, Pejman and Aguet, François and Zou, Yuxin and Khramtsova, Ekaterina A. and Skol, Andrew D. and Garrido-Martín, Diego and Reverter, Ferran and Brown, Andrew and Evans, Patrick and Gamazon, Eric R. and Payne, Anthony and Bonazzola, Rodrigo and Barbeira, Alvaro N. and Hamel, Andrew R. and Martinez-Perez, Angel and Soria, José Manuel and {GTEx Consortium} and Pierce, Brandon L. and Stephens, Matthew and Eskin, Eleazar and Dermitzakis, Emmanouil T. and Segrè, Ayellet V. and Im, Hae Kyung and Engelhardt, Barbara E. and Ardlie, Kristin G. and Montgomery, Stephen B. and Battle, Alexis J. and Lappalainen, Tuuli and Guigó, Roderic and Stranger, Barbara E.},\n\tmonth = sep,\n\tyear = {2020},\n}\n\n

\n\n\n\n\n\n

\n\n

\n \n 2019\n \n \n (1)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Ancient Rome: A genetic crossroads of Europe and the Mediterranean.\n \n \n \n \n\n\n \n Antonio, M. L.; Gao, Z.; Moots, H. M.; Lucci, M.; Candilio, F.; Sawyer, S.; Oberreiter, V.; Calderon, D.; Devitofranceschi, K.; Aikens, R. C.; Aneli, S.; Bartoli, F.; Bedini, A.; Cheronet, O.; Cotter, D. J.; Fernandes, D. M.; Gasperetti, G.; Grifoni, R.; Guidi, A.; La Pastina, F.; Loreti, E.; Manacorda, D.; Matullo, G.; Morretta, S.; Nava, A.; Fiocchi Nicolai, V.; Nomi, F.; Pavolini, C.; Pentiricci, M.; Pergola, P.; Piranomonte, M.; Schmidt, R.; Spinola, G.; Sperduti, A.; Rubini, M.; Bondioli, L.; Coppa, A.; Pinhasi, R.; and Pritchard, J. K.\n\n\n \n\n\n\n Science, 366(6466): 708–714. November 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Ancient$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{antonio_ancient_2019,\n\ttitle = {Ancient {Rome}: {A} genetic crossroads of {Europe} and the {Mediterranean}},\n\tvolume = {366},\n\tissn = {0036-8075},\n\turl = {https://science.sciencemag.org/content/366/6466/708},\n\tdoi = {10.1126/science.aay6826},\n\tabstract = {Ancient Rome was the capital of an empire of {\\textasciitilde}70 million inhabitants, but little is known about the genetics of ancient Romans. Here we present 127 genomes from 29 archaeological sites in and around Rome, spanning the past 12,000 years. We observe two major prehistoric ancestry transitions: one with the introduction of farming and another prior to the Iron Age. By the founding of Rome, the genetic composition of the region approximated that of modern Mediterranean populations. During the Imperial period, Rome’s population received net immigration from the Near East, followed by an increase in genetic contributions from Europe. These ancestry shifts mirrored the geopolitical affiliations of Rome and were accompanied by marked interindividual diversity, reflecting gene flow from across the Mediterranean, Europe, and North Africa.},\n\tnumber = {6466},\n\tjournal = {Science},\n\tauthor = {Antonio, Margaret L. and Gao, Ziyue and Moots, Hannah M. and Lucci, Michaela and Candilio, Francesca and Sawyer, Susanna and Oberreiter, Victoria and Calderon, Diego and Devitofranceschi, Katharina and Aikens, Rachael C. and Aneli, Serena and Bartoli, Fulvio and Bedini, Alessandro and Cheronet, Olivia and Cotter, Daniel J. and Fernandes, Daniel M. and Gasperetti, Gabriella and Grifoni, Renata and Guidi, Alessandro and La Pastina, Francesco and Loreti, Ersilia and Manacorda, Daniele and Matullo, Giuseppe and Morretta, Simona and Nava, Alessia and Fiocchi Nicolai, Vincenzo and Nomi, Federico and Pavolini, Carlo and Pentiricci, Massimo and Pergola, Philippe and Piranomonte, Marina and Schmidt, Ryan and Spinola, Giandomenico and Sperduti, Alessandra and Rubini, Mauro and Bondioli, Luca and Coppa, Alfredo and Pinhasi, Ron and Pritchard, Jonathan K.},\n\tmonth = nov,\n\tyear = {2019},\n\tpages = {708--714},\n}\n\n

\n\n\n\n\n\n

\n\n

\n \n 2016\n \n \n (1)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Genetic diversity on the human X chromosome does not support a strict pseudoautosomal boundary.\n \n \n \n \n\n\n \n Cotter, D. J.; Brotman, S. M.; and Wilson Sayres, M. A.\n\n\n \n\n\n\n Genetics, 203(1): 485–492. May 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Genetic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{cotter_genetic_2016,\n\ttitle = {Genetic diversity on the human {X} chromosome does not support a strict pseudoautosomal boundary},\n\tvolume = {203},\n\tcopyright = {Copyright © 2016 by the Genetics Society of America. Available freely online through the author-supported open access option.},\n\tissn = {0016-6731, 1943-2631},\n\turl = {http://www.genetics.org/content/203/1/485},\n\tdoi = {10.1534/genetics.114.172692},\n\tabstract = {Unlike the autosomes, recombination between the X chromosome and the Y chromosome is often thought to be constrained to two small pseudoautosomal regions (PARs) at the tips of each sex chromosome. PAR1 spans the first 2.7 Mb of the proximal arm of the human sex chromosomes, whereas the much smaller PAR2 encompasses the distal 320 kb of the long arm of each sex chromosome. In addition to PAR1 and PAR2, there is a human-specific X-transposed region that was duplicated from the X to the Y chromosome. The X-transposed region is often not excluded from X-specific analyses, unlike the PARs, because it is not thought to routinely recombine. Genetic diversity is expected to be higher in recombining regions than in nonrecombining regions because recombination reduces the effect of linked selection. In this study, we investigated patterns of genetic diversity in noncoding regions across the entire X chromosome of a global sample of 26 unrelated genetic females. We found that genetic diversity in PAR1 is significantly greater than in the nonrecombining regions (nonPARs). However, rather than an abrupt drop in diversity at the pseudoautosomal boundary, there is a gradual reduction in diversity from the recombining through the nonrecombining regions, suggesting that recombination between the human sex chromosomes spans across the currently defined pseudoautosomal boundary. A consequence of recombination spanning this boundary potentially includes increasing the rate of sex-linked disorders (e.g., de la Chapelle) and sex chromosome aneuploidies. In contrast, diversity in PAR2 is not significantly elevated compared to the nonPARs, suggesting that recombination is not obligatory in PAR2. Finally, diversity in the X-transposed region is higher than in the surrounding nonPARs, providing evidence that recombination may occur with some frequency between the X and Y chromosomes in the X-transposed region.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2018-05-15},\n\tjournal = {Genetics},\n\tauthor = {Cotter, Daniel J. and Brotman, Sarah M. and Wilson Sayres, Melissa A.},\n\tmonth = may,\n\tyear = {2016},\n\tpmid = {27010023},\n\tkeywords = {X-transposed region (XTR), genetics of sex, nucleotide diversity, pseudoautosomal region (PAR), recombination, sex chromosome evolution},\n\tpages = {485--492},\n}\n

\n\n\n\n\n\n

\n\n\n\n\n

\n\n\n \n\n \n \n \n \n\n