Ziheng Yang Explained

Ziheng Yang
Birth Place:Gansu, China
Citizenship:United Kingdom
Fields:molecular evolution
molecular phylogenetics
population genetics
computational biology
computational statistics
Markov chain Monte Carlo
Workplaces:University College London
Beijing Agricultural University
Alma Mater:Beijing Agricultural University
Known For:Models of DNA sequence evolution and methods of statistical inference in molecular evolution and phylogenetics
Awards:Darwin–Wallace Medal (2023)
Frink Medal (2010)
Royal Society Wolfson Research Merit Award (2009)
SSB Presidents' Award for Lifetime Achievement (2008)
Fellow of the Royal Society (2006)
Young Investigator’s Prize, American Society of Naturalists (1995)

Ziheng Yang FRS (; born 1 November 1964) is a Chinese biologist. He holds the R.A. Fisher Chair of Statistical Genetics[1] at University College London,[2] and is the Director of R.A. Fisher Centre for Computational Biology at UCL. He was elected a Fellow of the Royal Society in 2006.

Academic career

Yang graduated from Gansu Agricultural University with a BSc in 1984, and from Beijing Agricultural University with a MSc in 1987, and PhD in 1992.[3]

After the PhD, he worked as a postdoctoral researcher in Department of Zoology, University of Cambridge (1992–3), The Natural History Museum (London) (1993–4), Pennsylvania State University (1994–5), and University of California at Berkeley (1995–7), before taking up a faculty position in Department of Biology, University College London. He was a Lecturer (1997), Reader (2000), and then Professor (2001) in the same department. He was appointed to the R.A. Fisher Chair in Statistical Genetics in UCL in 2010.

Yang held a number of visiting appointments. He was a Visiting Associate Professor atInstitute of Statistical Mathematics (Tokyo, 1997–8), a visiting professor at University ofTokyo (2007–8), Institute of Zoology in Beijing (2010–1), PekingUniversity (2010), National Institute of Genetics, Mishima, Japan(2011), and Swiss Institute of Technology (ETH), Zurich (2011). In 2008–2011, he was the Changjiang Chair Professor at Sun Yat-sen University, with an award from the Ministry of Education of China. From 2016 to 2019, he was a visiting professor at National Institute of Genetics, Japan. In 2017–8, he was a Radcliffe Fellow at Harvard University's Radcliffe Institute for Advanced Study.[4]

Work in molecular evolution and phylogenetics

Yang developed a number of statistical models and methods in the 1990s, which have been implemented in maximum likelihood and Bayesian software programs for phylogenetic analysis of DNA and protein sequence data. Two decades ago, Felsenstein had described the pruning algorithm for calculating the likelihood on a phylogeny.[5] [6] However, the assumed model of character change was simple and, for example, does not account for variable rates among sites in the sequence. By illustrating the power of statistical models to accommodate major features of the evolutionary process and to address important evolutionary questions using molecular sequence data, the models and methods Yang developed had a major impact on the cladistic-statistical controversy at the time and played a major role in the transformation of molecular phylogenetics.

Yang developed a maximum likelihood model of gamma-distributed evolutionary rate variation among sites in the sequence in 1993–4.[7] [8] The models he developed for combined analysis of heterogeneous data [9] [10] are later known as partition models and mixture models.

Together with Nick Goldman, Yang developed the codon model of nucleotide substitution in 1994.[11] This formed the basis for phylogenetic analysis of protein-coding genes to detect molecular adaptation or Darwinian evolution at the molecular level. A stream of papers followed this to extend the original model to accommodate variable selection pressures (measured by the dN/dS ratio) among evolutionary lineages or among sites in the protein sequence. The branch models allow different branches to have different dN/dS ratios among branches on the tree and can be used to test for positive selection affecting particular lineages.[12] The site models allow different selective pressures on different amino acids in the protein and can be used to test for positive selection affecting only a few amino acid sites.[13] [14] [15] And the branch-site models attempt to detect positive selection that affects only a few amino acid sites along pre-specific lineages.[16] [15] A recent book reviews the recent developments in this area.[17]

Yang developed the statistical (empirical Bayes) method for reconstructing ancestral sequences in 1995.[18] Compared with the parsimony method of ancestral sequence reconstruction (that is, the Fitch–Hartigan algorithm),[19] [20] this has the advantages of using branch-length information and of providing a probabilistic assessment of the reconstruction uncertainties.

Together with Bruce Rannala, Yang introduced Bayesian statistics into molecular phylogenetics in 1996.[21] [22] The Bayesian is now one of the most popular statistical methodologies used in modeling and inference in molecular phylogenetics. Recent exciting developments in Bayesian phylogenetics are summarized in an edited book[23] and in chapter 8 of Yang's book.[24]

Yang and Rannala also developed the multispecies coalescent model,[25] which has emerged as the natural framework for comparative analysis of genomic sequence data from multiple species, incorporating the coalescent process in both modern species and extinct ancestors. The model has been used to estimate the species tree despite gene tree heterogeneity among genomic regions,[26] [27] [28] and to delimit/identify species.[29] Yang champions the Bayesian full-likelihood method of inference, using Markov chain Monte Carlo to average over gene trees (gene genealogies), accommodating phylogenetic uncertainties.

Yang maintains the program package PAML (for Phylogenetic Analysis by Maximum Likelihood)[30] and the Bayesian Markov chain Monte Carlo program BPP (for Bayesian Phylogenetics and Phylogeography).[31]

Work in principles of statistical inference and computational statistics

Yang studied the star tree paradox, which is that Bayesian model selection produces spuriously high posterior probabilities for the binary trees if the data are simulated under the star tree.[32] [33] A simpler case showing similar behaviours is the fair-coin paradox. The work suggests that Bayesian model selection may produce unpleasant polarized behavior supporting one model with full force while rejecting the others, when the competing models are all misspecified and equally wrong.[34]

Yang has worked extensively on Markov chain Monte Carlo algorithms, deriving many Metropolis-Hastings algorithms in Bayesian phylogenetics.[35] A study examining the efficiency of simple MCMC proposals revealed that the well-studied Gaussian random-walk move is less efficient than the simple uniform random-walk move, which is in turn less efficient than the Bactrian moves, bimodal moves that suppress values very close to the current state.[36]

Professional activities

Yang taught in Woods Hole Workshop on Molecular Evolution.

He was a co-organizer of the Royal Society Discussion Meeting on "Statistical and computational challenges in molecular phylogenetics and evolution" on 28–29 April 2008,[37] and the Royal Society Discussion Meeting on "Dating species divergence using rocks and clocks", on 9–10 November 2015.[38]

Since 2009, he has been a co-organizer of an annual workshop on Computational Molecular Evolution (CoME), which has been running in Sanger/Hinxton in odd years and in Hiraklion, Crete in even years.http://abacus.gene.ucl.ac.uk/meetings/CoME/

He also organized and taught in a number of workshops in Beijing, China.

Awards and honours

2023-2025, President, Society for Molecular Biology and Evolution https://www.smbe.org/smbe/ABOUT/Council.aspx

2023, Darwin–Wallace Medal, Linnean Society of London[39]

2010, Frink Medal for British Zoologists, Zoological Society of London[40]

2009, Royal Society Wolfson Research Merit Award

2008, President's Award for Lifetime Achievement, Society for Systematic Biology [41]

2006, Fellow of the Royal Society, The Royal Society of London https://royalsociety.org/people/ziheng-yang-12576/

1995, Young Investigator’s Prize, American Society of Naturalists http://www.amnat.org/awards.html#Jasper

Books

External links

Notes and References

  1. Web site: Genetics, Evolution and Environment . Ucl.ac.uk . 2017-06-23.
  2. ‘YANG, Prof. Ziheng’, Who's Who 2011, A & C Black, 2011; online edn, Oxford University Press, Dec 2010; online edn, Oct 2010 accessed 11 May 2011
  3. Web site: Iris View Profile. Iris.ucl.ac.uk. 2017-06-23.
  4. Web site: Ziheng Yang Radcliffe Institute for Advanced Study at Harvard University. www.radcliffe.harvard.edu. en. 2017-12-01.
  5. Felsenstein. Joe. 1973. Maximum likelihood and minimum-steps methods for estimating evolutionary trees from data on discrete characters. Syst. Zool.. 22. 3. 240–249. 10.2307/2412304. 2412304.
  6. Felsenstein. Joe. 1981. Evolutionary trees from DNA sequences: a maximum likelihood approach. J. Mol. Evol.. 17. 6. 368–376. 10.1007/bf01734359. 7288891. 1981JMolE..17..368F. 8024924.
  7. Yang. Ziheng. 1993. Maximum-likelihood estimation of phylogeny from DNA sequences when substitution rates differ over sites. Mol. Biol. Evol.. 10. 6. 1396–1401. 10.1093/oxfordjournals.molbev.a040082. 8277861. free.
  8. Yang . Z . 1994 . Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods . J Mol Evol . 39 . 3. 306–314 . 10.1007/bf00160154 . 1994JMolE..39..306Y. 10.1.1.305.951 . 7932792 . 17911050 .
  9. Yang Z, Lauder IJ, Lin HJ. 1995. Molecular evolution of the hepatitis B virus genome. J. Mol. Evol.. 41. 5. 587–596. 10.1007/bf00175817. 7490773. 1995JMolE..41..587Y. 9176917.
  10. Yang Z.. 1996. Maximum-likelihood models for combined analyses of multiple sequence data. J. Mol. Evol.. 42. 5. 587–596. 10.1007/bf02352289. 8662011. 1996JMolE..42..587Y. 10.1.1.19.6773. 12660243.
  11. Goldman N, Yang Z . 1994. A codon-based model of nucleotide substitution for protein-coding DNA sequences. Mol Biol Evol. 11. 5. 725–736. 10.1093/oxfordjournals.molbev.a040153 . 7968486. free.
  12. Yang. Ziheng. 1998. Likelihood ratio tests for detecting positive selection and application to primate lysozyme evolution. Mol. Biol. Evol.. 15. 5. 568–573. 10.1093/oxfordjournals.molbev.a025957. 9580986. free.
  13. Nielsen, R. . Yang, Z.. 1998. Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene. Genetics. 148. 3. 929–936. 10.1093/genetics/148.3.929. 9539414. 1460041.
  14. Yang, Z. . Nielsen, R. . Goldman, N. . Pedersen, A.-M.K.. 2000. Codon-substitution models for heterogeneous selection pressure at amino acid sites. Genetics. 155. 1. 431–449. 10.1093/genetics/155.1.431. 10790415. 1461088.
  15. Yang. Ziheng. Wong. Wendy S. W.. Nielsen. Rasmus. 2005-04-01. Bayes Empirical Bayes Inference of Amino Acid Sites Under Positive Selection. Molecular Biology and Evolution. 22. 4. 1107–1118. 10.1093/molbev/msi097. 15689528. 0737-4038. free.
  16. Yang, Z. . Nielsen, R.. 2002. Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol. Biol. Evol.. 19. 6. 908–917. 10.1093/oxfordjournals.molbev.a004148. 12032247. free. 1813/32161. free.
  17. Book: Codon evolution : mechanisms and models. 2012. Oxford University Press . Cannarozzi, Gina M. . Schneider, Adrian . 9780199601165. Oxford. 784949340.
  18. Yang Z, Kumar S, Nei M . 1995. A new method of inference of ancestral nucleotide and amino acid sequences. Genetics. 141. 4. 1641–1650. 10.1093/genetics/141.4.1641. 8601501. 1206894.
  19. Fitch. Walter M.. 1971. Toward defining the course of evolution: minimum change for a specific tree topology. Syst. Zool.. 20. 4. 406–416. 10.2307/2412116. 2412116.
  20. Hartigan, J.A.. 1973. Minimum evolution fits to a given tree. Biometrics. 29. 1. 53–65. 10.2307/2529676. 2529676.
  21. Rannala B, Yang Z . 1996. Probability distribution of molecular evolutionary trees: a new method of phylogenetic inference. J. Mol. Evol.. 43. 3. 304–311. 10.1007/bf02338839. 1996JMolE..43..304R. 8703097. 8269826.
  22. Yang Z, Rannala B . 1997. Bayesian phylogenetic inference using DNA sequences: a Markov chain Monte Carlo Method. Mol. Biol. Evol.. 14. 7. 717–724. 10.1093/oxfordjournals.molbev.a025811. 9214744. free.
  23. Book: Bayesian phylogenetics : methods, algorithms, and applications . Chen, Ming-Hui . Kuo, Lynn . Lewis, Paul O. . 9781466500792. Boca Raton . Chapman & Hall/CRC. 881387408 . 2014-05-27.
  24. Book: Ziheng, Yang. Molecular evolution : a statistical approach. 9780199602605. First. Oxford. Oxford University Press. 869346345. 2014.
  25. Rannala B, Yang Z . 2003. Bayes estimation of species divergence times and ancestral population sizes using DNA sequences from multiple loci. Genetics. 164. 4. 1645–1656. 10.1093/genetics/164.4.1645. 12930768. 1462670.
  26. Yang. Ziheng. Rannala. Bruce. 2014-12-01. Unguided Species Delimitation Using DNA Sequence Data from Multiple Loci. Molecular Biology and Evolution. 31. 12. 3125–3135. 10.1093/molbev/msu279. 0737-4038. 4245825. 25274273.
  27. Rannala. Bruce. Yang. Ziheng. 2017-09-01. Efficient Bayesian Species Tree Inference under the Multispecies Coalescent. Systematic Biology. 66. 5. 823–842. 10.1093/sysbio/syw119. 28053140. 8562347 . 1063-5157. 1512.03843. 3554064.
  28. Xu. Bo. Yang. Ziheng. 2016-12-01. Challenges in Species Tree Estimation Under the Multispecies Coalescent Model. Genetics. en. 204. 4. 1353–1368. 10.1534/genetics.116.190173. 0016-6731. 27927902. 5161269.
  29. Yang. Ziheng. Rannala. Bruce. 2010-05-18. Bayesian species delimitation using multilocus sequence data. Proceedings of the National Academy of Sciences. en. 107. 20. 9264–9269. 10.1073/pnas.0913022107. 0027-8424. 20439743. 2889046. 2010PNAS..107.9264Y. free.
  30. Yang. Ziheng. 2007. PAML 4: Phylogenetic analysis by maximum likelihood. Mol. Biol. Evol.. 24. 8. 1586–1591. 10.1093/molbev/msm088. 17483113. free.
  31. Yang. Ziheng. 2015-10-01. The BPP program for species tree estimation and species delimitation. Current Zoology. 61. 5. 854–865. 10.1093/czoolo/61.5.854. 1674-5507. free.
  32. Yang. Ziheng. Rannala. Bruce. Lewis. Paul. 2005-06-01. Branch-Length Prior Influences Bayesian Posterior Probability of Phylogeny. Systematic Biology. en. 54. 3. 455–470. 10.1080/10635150590945313. 16012111. 1063-5157. free.
  33. Yang. Ziheng. 2007-08-01. Fair-Balance Paradox, Star-tree Paradox, and Bayesian Phylogenetics. Molecular Biology and Evolution. 24. 8. 1639–1655. 10.1093/molbev/msm081. 17488737. 0737-4038. free.
  34. Yang. Ziheng. Zhu. Tianqi. Bayesian selection of misspecified models is overconfident and may cause spurious posterior probabilities for phylogenetic trees. Proceedings of the National Academy of Sciences. 115. 8. 5 February 2018. 1854–1859. 10.1073/pnas.1712673115. 29432193. 5828583. 2018PNAS..115.1854Y . free.
  35. Book: Ziheng, Yang. Molecular evolution : a statistical approach. 9780199602612. First. Oxford. Oxford University Press. 869346345. 2014.
  36. Yang. Ziheng. Rodríguez. Carlos E.. 2013-11-26. Searching for efficient Markov chain Monte Carlo proposal kernels. Proceedings of the National Academy of Sciences. en. 110. 48. 19307–19312. 10.1073/pnas.1311790110. 0027-8424. 24218600. 3845170. 2013PNAS..11019307Y. free.
  37. Web site: Statistical and computational challenges in molecular phylogenetics and evolution. Royal Society.
  38. Web site: Dating species divergences using rocks and clocks. Royal Society.
  39. Web site: The Darwin-Wallace Medal. 2023-06-09.
  40. Web site: Winners of the ZSL Frink Medal for British Zoologists. Static.zsl.org. 2017-06-23.
  41. Web site: Society of Systematic Biologists (SSB). Society of Systematic Biologists.