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Ka/Ks ratio

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addition, in the example above two non-synonymous and one synonymous substitution occurred at the third site; however, because substitutions restored the original sequence, there is no evidence of any substitution. As the divergence time between two sequences increases, so too does the amount of multiple substitutions. Thus "long branches" in a dN/dS analysis can lead to underestimates of both dN and dS, and the longer the branch, the harder it is to correct for the introduced noise. Of course, the ancestral sequence is usually unknown, and two lineages being compared will have been evolving in parallel since their last common ancestor. This effect can be mitigated by constructing the ancestral sequence; the accuracy of this sequence is enhanced by having a large number of sequences descended from that common ancestor to constrain its sequence by
529:, which is coded by the codons AAT or AAC, a high C->T exchange rate will increase the proportion of synonymous substitutions at this codon, whereas a high C→A exchange rate will increase the rate of non-synonymous substitutions. Because it is rather common for transitions (T↔C & A↔G) to be favoured over transversions (other changes), models must account for the possibility of non-homogeneous rates of exchange. Some simpler approximate methods, such as those of Miyata & Yasunaga and Nei & Gojobori, neglect to take these into account, which generates a faster computational time at the expense of accuracy; these methods will systematically overestimate N and underestimate S. 676:
ratio at specific codons within a gene sequence. For instance, the frequency-tuning region of an opsin may be under enhanced selective pressure when a species colonises and adapts to new environment, whereas the region responsible for initializing a nerve signal may be under purifying selection. In
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are chemically similar to one another, whereas other substitutions may place an amino acid with wildly different properties to its precursor. In most situations, a smaller chemical change is more likely to allow the protein to continue to function, and a large chemical change is likely to disrupt the
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In addition, as time progresses, it is possible for a site to undergo multiple modifications. For instance, a codon may switch from AAA→AAC→AAT→AAA. There is no way of detecting multiple substitutions at a single site, thus the estimate of the number of substitutions is always an underestimate. In
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An additional concern is that the effects of time must be incorporated into an analysis, if the lineages being compared are closely related; this is because it can take a number of generations for natural selection to "weed out" deleterious mutations from a population, especially if their effect on
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Of course, it is necessary to perform a statistical analysis to determine whether a result is significantly different from 1, or whether any apparent difference may occur as a result of a limited data set. The appropriate statistical test for an approximate method involves approximating dN −
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Approximate methods involve three basic steps: (1) counting the number of synonymous and nonsynonymous sites in the two sequences, or estimating this number by multiplying the sequence length by the proportion of each class of substitution; (2) counting the number of synonymous and nonsynonymous
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acting on protein coding genes. A ratio greater than 1 implies positive or Darwinian selection (driving change); less than 1 implies purifying or stabilizing selection (acting against change); and a ratio of exactly 1 indicates neutral (i.e. no) selection. However, a combination of positive and
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Further, there may be a bias in which certain codons are preferred in a gene, as a certain combination of codons may improve translational efficiency. A 2022 study reported that synonymous mutations in representative yeast genes are mostly strongly non-neutral, which calls into question the
409:, and counting methods. However, unless the sequences to be compared are distantly related (in which case maximum-likelihood methods prevail), the class of method used makes a minimal impact on the results obtained; more important are the assumptions implicit in the chosen method. 720:> 1 are candidates to be experiencing positive selection. This form of test can either identify sites that further laboratory research can examine to determine possible selective pressure; or, sites believed to have functional significance can be assigned into different K 443:
In order to quantify the number of substitutions, one may reconstruct the ancestral sequence and record the inferred changes at sites (straight counting – likely to provide an underestimate); fitting the substitution rates at sites into predetermined categories
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chemical structure and cause the protein to malfunction. However, incorporating this into a model is not straightforward as the relationship between a nucleotide substitution and the effects of the modified chemical properties is very difficult to determine.
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purifying selection at different points within the gene or at different times along its evolution may cancel each other out. The resulting averaged value can mask the presence of one of the selections and lower the seeming magnitude of another selection.
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dS with a normal approximation, and determining whether 0 falls within the central region of the approximation. More sophisticated likelihood techniques can be used to analyse the results of a Maximum Likelihood analysis, by performing a
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These steps, particularly the latter, require simplistic assumptions to be made if they are to be achieved computationally; for reasons discussed later, it is impossible to exactly determine the number of multiple substitutions.
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to complete all three steps simultaneously. It estimates critical parameters, including the divergence between sequences and the transition/transversion ratio, by deducing the most likely values to produce the input data.
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ratio is a good indicator of selective pressure at the sequence level, evolutionary change can often take place in the regulatory region of a gene which affects the level, timing or location of gene expression.
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in a protein chain. However, there are more codons (64) than amino acids found in proteins (20), so many codons are effectively synonyms. For example, the DNA codons TTT and TTC both code for the amino acid
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analysis will not detect such change. It will only calculate selective pressure within protein coding regions. In addition, selection that does not cause differences at an amino acid level—for instance,
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method requires a rather strong signal in order to detect selection. In order to detect selection between lineages, then the selection, averaged over all sites in the sequence, must produce a K
157:, so a change from the middle A to T does change the resulting protein, for better or (more likely) worse, so the change is not a synonym. These changes are illustrated in the tables below. 525:
are swapped, as certain mutations are more probable than others. For instance, some lineages may swap C to T more frequently than they swap C to A. In the case of the amino acid
405:(rather than being genetic switches, controlling development or the rate of activity of other genes). Methods can be classified into three groups: approximate methods, 1094:
Rocha EP, Smith JM, Hurst LD, Holden MT, Cooper JE, Smith NH, Feil EJ (March 2006). "Comparisons of dN/dS are time dependent for closely related bacterial genomes".
831:"Better" means that the change is advantageous and will be selected for by natural selection. "Worse" means that the change is harmful, and will be selected against. 84:), in the same period. The latter are assumed to be neutral, so that the ratio indicates the net balance between deleterious and beneficial mutations. Values of K 1488:"A new method for estimating synonymous and nonsynonymous rates of nucleotide substitution considering the relative likelihood of nucleotide and codon changes" 593:= 1, it could be due to relaxed selection, or to a chimera of positive and purifying selection at the locus. A solution to this limitation would be to apply K 1830: 640:
rate to take multiple values across sites and across lineages; the inclusion of more lineages also increases the power of a sites-based approach.
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at that site—implying that the site must be under selective pressure in all sampled lineages. This limitation can be moderated by allowing the K
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Kosakovsky Pond SL, Frost SD (May 2005). "Not so different after all: a comparison of methods for detecting amino acid sites under selection".
61: 1523:"A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome" 552:
Methods that account for biases in codon usage and transition/transversion rates are substantially more reliable than those that do not.
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greater than one—quite a feat if regions of the gene are strongly conserved. In order to detect selection at specific sites, then the K
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Yang Z, Nielsen R (January 2000). "Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models".
1823: 149:, so a change from the third T to C makes no difference to the resulting protein. On the other hand, the codon GAG codes for 1290:
Comeron JM (December 1995). "A method for estimating the numbers of synonymous and nonsynonymous substitutions per site".
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Further, the method lacks the capability to distinguish between positive and negative nonsynonymous substitutions. Some
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to exceed 1 in some sites improves the fit of the model. If this is the case, then sites fitting into the class where K
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Goldman N, Yang Z (September 1994). "A codon-based model of nucleotide substitution for protein-coding DNA sequences".
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Ina Y (February 1995). "New methods for estimating the numbers of synonymous and nonsynonymous substitutions".
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SeqinR: A free and open biological sequence analysis package for the R language that includes KaKs calculation
452:(computationally expensive). Given enough data, all three of these approaches will tend to the same result. 1952: 1896: 215: 177: 77: 910: 704:
ratio is constrained to be < 1 in all sites to one where it may take any value, and see if permitting K
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Another issue is that heterogeneity within a gene can make a result hard to interpret. For example, if K
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Li WH (January 1993). "Unbiased estimation of the rates of synonymous and nonsynonymous substitution".
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The first step in identifying whether positive selection acts on sites is to compare a test where the K
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are count estimates, which represent the total numbers of non-synonymous and synonymous substitutions.
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ratio measures the relative rates of synonymous and nonsynonymous substitutions at a particular site.
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ratio is a more powerful test of the neutral model of evolution than many others available in
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ratio at each site. However this is computationally expensive and in practise, a number of K
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approach; poor for small data sets); and generating an individual substitution rate for each
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being advantageous. If beneficial mutations are assumed to make little contribution, then K
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Hurst LD (September 2002). "The Ka/Ks ratio: diagnosing the form of sequence evolution".
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Hurst LD (September 2002). "The Ka/Ks ratio: diagnosing the form of sequence evolution".
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Selection acts on variation in phenotypes, which are often the result of mutations in
1972: 1916: 1483: 1080: 357: 262: 253: 150: 146: 129: 1745:"KaKs_Calculator: calculating Ka and Ks through model selection and model averaging" 1475: 1430: 1327: 1031:"Synonymous mutations in representative yeast genes are mostly strongly non-neutral" 546: 307: 205: 125: 1593:"Evolution of the Zfx and Zfy genes: rates and interdependence between the genes" 1155: 1692:"Computing Ka and Ks with a consideration of unequal transitional substitutions" 1115: 1054: 16:
Ratio estimating the balance between nonsynonymous and synonymous substitutions
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classes are established, and each site is assigned to the best-fitting class.
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Free online server tool that calculates KaKs ratios among multiple sequences
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significantly above 1 are unlikely to occur without at least some of the
20: 1798: 1459: 1414: 1311: 402: 352: 248: 117: 1808: 1239:"Why time matters: codon evolution and the temporal dynamics of dN/dS" 366: 154: 449: 369:            303: 201: 133: 121: 1812: 1743:
Zhang Z, Li J, Zhao XQ, Wang J, Wong GK, Yu J (November 2006).
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order to detect such effects, one would ideally calculate the K
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ratio must be greater than one when averaged over all included
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substitutions; and (3) correcting for multiple substitutions.
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Additional information can be gleaned by determining the K
899:"Statistical methods for detecting molecular adaptation" 468:
ratio is used to infer the direction and magnitude of
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fitness is weak. This limits the usefulness of the K
1930: 1889: 1846: 601:analysis across many species at individual codons. 660:ratio for comparing closely related populations. 68:. It is calculated as the ratio of the number of 76:), in a given period of time, to the number of 1824: 8: 1137:Kryazhimskiy S, Plotkin JB (December 2008). 766:are used interchangeably. Note however that 64:and beneficial mutations acting on a set of 1029:Shen X, Song S, Li C, Zhang J (June 2022). 989: 987: 892: 890: 888: 886: 884: 882: 880: 1831: 1817: 1809: 878: 876: 874: 872: 870: 868: 866: 864: 862: 860: 372:Altered protein may or may not cause harm 56:, is used to estimate the balance between 1768: 1749:Genomics, Proteomics & Bioinformatics 1725: 1715: 1643: 1608: 1573: 1538: 1503: 1262: 1237:Mugal CF, Wolf JB, Kaj I (January 2014). 1213: 1164: 1154: 1062: 932: 914: 582:—cannot be detected by these techniques. 1632:Computer Applications in the Biosciences 272: 170: 856: 737: 397:of two or more nucleotide sequences of 1188:Peterson GI, Masel J (November 2009). 897:Yang Z, Bielawski JP (December 2000). 481:to distinguish between a null model (K 1675:10.1093/oxfordjournals.molbev.a026236 1610:10.1093/oxfordjournals.molbev.a040003 1575:10.1093/oxfordjournals.molbev.a040410 1540:10.1093/oxfordjournals.molbev.a040152 1505:10.1093/oxfordjournals.molbev.a040343 1349:10.1093/oxfordjournals.molbev.a040153 430:The maximum-likelihood approach uses 374:(e.g. disease) or give new advantage 7: 1556:Nei M, Gojobori T (September 1986). 1591:Pamilo P, Bianchi NO (March 1993). 1521:Muse SV, Gaut BS (September 1994). 533:assumptions underlying use of the K 1139:"The population genetics of dN/dS" 521:in the frequency at which various 509:as it requires fewer assumptions. 14: 1902:Models of nucleotide substitution 1690:Zhang Z, Li J, Yu J (June 2006). 903:Trends in Ecology & Evolution 728:classes before the model is run. 140:. Each codon represents a single 267:Normal protein, normal function 1663:Molecular Biology and Evolution 1645:10.1093/bioinformatics/13.5.555 1597:Molecular Biology and Evolution 1562:Molecular Biology and Evolution 1527:Molecular Biology and Evolution 1492:Molecular Biology and Evolution 1337:Molecular Biology and Evolution 1243:Molecular Biology and Evolution 1194:Molecular Biology and Evolution 958:Molecular Biology and Evolution 489:= 1) and the observed results. 66:homologous protein-coding genes 1486:, Wu CI, Luo CC (March 1985). 1440:Journal of Molecular Evolution 1395:Journal of Molecular Evolution 1292:Journal of Molecular Evolution 1096:Journal of Theoretical Biology 780:are different parameters from 153:while the codon GTG codes for 1: 1761:10.1016/S1672-0229(07)60007-2 1378:10.1016/S0168-9525(02)02722-1 1008:10.1016/S0168-9525(02)02722-1 925:10.1016/S0169-5347(00)01994-7 1156:10.1371/journal.pgen.1000304 70:nonsynonymous substitutions 2005: 1958:Nonsynonymous substitution 1116:10.1016/j.jtbi.2005.08.037 1055:10.1038/s41586-022-04823-w 426:Maximum-likelihood methods 407:maximum-likelihood methods 321:Nonsynonymous substitution 280:nonsynonymous substitution 72:per non-synonymous site (K 664:Individual codon approach 1696:BMC Evolutionary Biology 840:Often but not always a " 385:Methods for estimating K 104:estimates the degree of 78:synonymous substitutions 1953:Synonymous substitution 1897:Models of DNA evolution 1626:Yang Z (October 1997). 216:Synonymous substitution 178:synonymous substitution 106:evolutionary constraint 1717:10.1186/1471-2148-6-44 80:per synonymous site (K 1876:Stabilizing selection 1861:Directional selection 1255:10.1093/molbev/mst192 1206:10.1093/molbev/msp175 970:10.1093/molbev/msi105 1866:Disruptive selection 456:Interpreting results 401:genes that code for 1979:Molecular evolution 1931:Molecular processes 1856:Balancing selection 1840:Molecular evolution 1708:2006BMCEE...6...44Z 1452:1993JMolE..36...96L 1407:1995JMolE..40..190I 1304:1995JMolE..41.1152C 1108:2006JThBi.239..226R 1047:2022Natur.606..725S 580:balancing selection 507:population genetics 413:Approximate methods 282: 180: 62:purifying selection 1989:Statistical ratios 1871:Negative selection 1460:10.1007/bf02407308 1415:10.1007/bf00167113 1366:Trends in Genetics 1312:10.1007/bf00173196 996:Trends in Genetics 432:probability theory 395:sequence alignment 273: 218:    213:harmless mutation; 171: 136:, groups of three 1966: 1965: 1848:Natural selection 1200:(11): 2595–2603. 1041:(7915): 725–731. 517:There is often a 470:natural selection 378: 377: 363:structural change 316:Missense mutation 286:Type of structure 271: 270: 184:Type of structure 58:neutral mutations 1996: 1943:Gene duplication 1907:Allele frequency 1833: 1826: 1819: 1810: 1782: 1772: 1739: 1729: 1719: 1686: 1657: 1647: 1622: 1612: 1587: 1577: 1552: 1542: 1517: 1507: 1479: 1434: 1389: 1360: 1331: 1298:(6): 1152–1159. 1277: 1276: 1266: 1234: 1228: 1227: 1217: 1185: 1179: 1178: 1168: 1158: 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301: 297: 294: 291: 288: 285: 284: 281: 277: 266: 264: 263:Phenylalanine 261: 258: 255: 254:Phenylalanine 252: 250: 246: 243: 242: 239: 236: 233: 230: 227: 226: 223: 220: 217: 212: 209: 207: 203: 200: 199: 195: 192: 189: 186: 183: 182: 179: 175: 169: 158: 156: 152: 151:Glutamic acid 148: 147:Phenylalanine 143: 139: 135: 131: 130:DNA sequences 127: 123: 119: 111: 109: 107: 95: 79: 71: 67: 63: 59: 55: 50: 43: 38: 34: 22: 1911: 1752: 1748: 1699: 1695: 1669:(1): 32–43. 1666: 1662: 1635: 1631: 1600: 1596: 1565: 1561: 1530: 1526: 1495: 1491: 1446:(1): 96–99. 1443: 1439: 1398: 1394: 1369: 1365: 1340: 1336: 1295: 1291: 1246: 1242: 1232: 1197: 1193: 1183: 1146: 1142: 1132: 1099: 1095: 1089: 1038: 1034: 1024: 999: 995: 961: 957: 951: 906: 902: 836: 827: 816: 809: 802: 795: 788: 781: 774: 767: 760: 753: 740: 695: 667: 650: 642: 629: 603: 584: 559: 551: 547:phylogenetic 543: 531: 516: 496: 475: 459: 442: 429: 420: 416: 384: 360:   308:DNA sequence 256:   206:DNA sequence 159: 126:genetic code 115: 48: 41: 40: 36: 24: 18: 1912:Ka/Ks ratio 744:The terms K 645:amino acids 556:Limitations 523:nucleotides 341:↓ codes for 335:↓ codes for 332:↓ codes for 237:↓ codes for 231:↓ codes for 228:↓ codes for 138:nucleotides 1973:Categories 1917:Tajima's D 852:References 527:Asparagine 399:homologous 349:Amino acid 278:causing a 245:Amino acid 176:causing a 142:amino acid 1702:(1): 44. 1081:249520936 911:CiteSeerX 549:methods. 259:no change 94:mutations 1984:Genetics 1779:17531802 1736:16740169 1683:10666704 1476:21618703 1431:25430897 1386:12175810 1328:19262479 1273:24129904 1224:19661199 1175:19081788 1124:16239014 1073:35676473 1016:12175810 978:15703242 943:11114436 630:lineages 541:ratio. 446:Bayesian 403:proteins 120:-coding 21:genetics 1770:5054075 1727:1552089 1704:Bibcode 1654:9367129 1619:8487630 1584:3444411 1549:7968485 1514:3916709 1468:8433381 1448:Bibcode 1423:7699723 1403:Bibcode 1357:7968486 1320:8587111 1300:Bibcode 1264:3879453 1215:2912466 1166:2596312 1104:Bibcode 1064:9650438 1043:Bibcode 934:7134603 493:Utility 381:Methods 353:Protein 298:Result 249:Protein 196:Result 118:protein 112:Context 1890:Models 1777:  1767:  1734:  1724:  1681:  1652:  1617:  1582:  1547:  1512:  1474:  1466:  1429:  1421:  1384:  1355:  1326:  1318:  1271:  1261:  1222:  1212:  1173:  1163:  1122:  1079:  1071:  1061:  1035:Nature 1014:  976:  941:  931:  913:  393:use a 367:Valine 338:  292:Change 289:Before 234:  190:Change 187:Before 155:Valine 134:codons 124:. The 23:, the 1484:Li WH 1472:S2CID 1427:S2CID 1324:S2CID 1077:S2CID 732:Notes 604:The K 497:The K 460:The K 450:codon 389:and K 351:in a 306:in a 304:Codon 295:After 247:in a 204:in a 202:Codon 193:After 160:The K 122:genes 54:ratio 33:ratio 1775:PMID 1732:PMID 1679:PMID 1650:PMID 1615:PMID 1580:PMID 1545:PMID 1510:PMID 1464:PMID 1419:PMID 1382:PMID 1353:PMID 1316:PMID 1269:PMID 1220:PMID 1171:PMID 1120:PMID 1069:PMID 1012:PMID 974:PMID 939:PMID 815:and 801:and 794:(or 787:and 773:and 752:and 1765:PMC 1757:doi 1722:PMC 1712:doi 1671:doi 1640:doi 1605:doi 1570:doi 1535:doi 1500:doi 1456:doi 1411:doi 1374:doi 1345:doi 1308:doi 1259:PMC 1251:doi 1210:PMC 1202:doi 1161:PMC 1151:doi 1112:doi 1100:239 1059:PMC 1051:doi 1039:606 1004:doi 966:doi 929:PMC 921:doi 808:). 325:GTG 312:GAG 221:TTC 210:TTT 132:as 39:or 19:In 1975:: 1773:. 1763:. 1751:. 1747:. 1730:. 1720:. 1710:. 1698:. 1694:. 1677:. 1667:17 1665:. 1648:. 1636:13 1634:. 1630:. 1613:. 1601:10 1599:. 1595:. 1578:. 1564:. 1560:. 1543:. 1531:11 1529:. 1525:. 1508:. 1494:. 1490:. 1470:. 1462:. 1454:. 1444:36 1442:. 1425:. 1417:. 1409:. 1399:40 1397:. 1380:. 1370:18 1368:. 1351:. 1341:11 1339:. 1322:. 1314:. 1306:. 1296:41 1294:. 1267:. 1257:. 1247:31 1245:. 1241:. 1218:. 1208:. 1198:26 1196:. 1192:. 1169:. 1159:. 1145:. 1141:. 1118:. 1110:. 1098:. 1075:. 1067:. 1057:. 1049:. 1037:. 1033:. 1010:. 1000:18 998:. 986:^ 972:. 962:22 960:. 937:. 927:. 919:. 907:15 905:. 901:. 859:^ 844:". 748:/K 724:/K 716:/K 708:/K 700:/K 689:/K 681:/K 672:/K 656:/K 636:/K 624:/K 616:/K 608:/K 597:/K 589:/K 573:/K 564:/K 537:/K 501:/K 485:/K 464:/K 274:A 172:A 164:/K 108:. 100:/K 88:/K 60:, 29:/K 1832:e 1825:t 1818:v 1781:. 1759:: 1753:4 1738:. 1714:: 1706:: 1700:6 1685:. 1673:: 1656:. 1642:: 1621:. 1607:: 1586:. 1572:: 1566:3 1551:. 1537:: 1516:. 1502:: 1496:2 1478:. 1458:: 1450:: 1433:. 1413:: 1405:: 1388:. 1376:: 1359:. 1347:: 1330:. 1310:: 1302:: 1275:. 1253:: 1226:. 1204:: 1177:. 1153:: 1147:4 1126:. 1114:: 1106:: 1083:. 1053:: 1045:: 1018:. 1006:: 980:. 968:: 945:. 923:: 820:s 817:D 813:n 810:D 806:S 803:K 799:A 796:K 792:S 789:d 785:N 782:d 778:s 775:D 771:n 768:D 764:S 761:d 759:/ 757:N 754:d 750:s 746:a 726:s 722:a 718:s 714:a 710:s 706:a 702:s 698:a 691:s 687:a 683:s 679:a 674:s 670:a 658:s 654:a 638:s 634:a 626:s 622:a 618:s 614:a 610:s 606:a 599:s 595:a 591:s 587:a 575:s 571:a 569:K 566:s 562:a 539:s 535:a 503:s 499:a 487:s 483:a 466:s 462:a 444:( 391:s 387:a 318:; 166:s 162:a 102:s 98:a 90:s 86:a 82:s 74:a 52:S 49:d 47:/ 45:N 42:d 37:ω 31:s 27:a 25:K

Index

genetics
neutral mutations
purifying selection
homologous protein-coding genes
nonsynonymous substitutions
synonymous substitutions
mutations
evolutionary constraint
protein
genes
genetic code
DNA sequences
codons
nucleotides
amino acid
Phenylalanine
Glutamic acid
Valine
point mutation
synonymous substitution
Codon
DNA sequence
Synonymous substitution
Amino acid
Protein
Phenylalanine
Phenylalanine
point mutation
nonsynonymous substitution
Codon

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