425:
and are themselves sometimes identified through genetic barcoding (usually of the CO1 region). Every insect that visits a flower is not necessarily a pollinator. Many lack features such as hairs allowing them to carry pollen while others avoid the pollen-laden anthers to steal nectar. Pollination networks are made more accurate by including what pollen is being carried by which insects. Some scientists argue that pollination effectiveness (PE), which is measured by studying the germination rates of seeds produced from flowers visited only once by a single animal, is the best way to determine which animals are important pollinators though other scientists have used DNA barcoding to determine the genetic origin of pollen found on insects and have argued that this in conjunction with other traits is a good indication of pollination effectiveness. By studying the composition and structure of pollination networks,
353:. The skills required to do DNA barcoding are much more common making the approach easier to adopt. Pollen DNA barcoding is a technique that has grown in popularity due to the decreased costs associated with "next generation sequencing" (NGS) techniques and is being continually improved in efficiency including through the use of a dual-indexing approach. Some of the other major advantages include the savings in time and resources compared to microscopic identification. Identifying pollen is time-consuming, involving spreading pollen on a slide, staining the pollen to improve visibility, then focusing in on individual pollen grains and identifying them based on size, shape, as well as the shape and number of pores. If a pollen reference library is not available, then pollen has to be collected from wild specimens or from
408:
304:
20:
120:
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which are made up of all the interactions between plants and the animals that facilitate their pollination. Identifying the pollen carried on insects helps scientists understand what plants are being visited by which insects. Insects can also have homologous features making them difficult to identify
432:
Another advantage of pollen DNA barcoding is that it can be used to determine the source of pollen found on museum specimens of insects, and these records of insect-plant interactions can then be compared to modern-day interactions to see how pollination networks have changed over time due to global
398:
There have been several different regions of plant DNA that have been used as targets for genetic barcoding including rbcL, matK, trnH-psbA, ITS1 and ITS2. A combination of rbcL and matK has been recommended for use in plant DNA barcoding. It has been found that trnL is better for degraded DNA and
348:
Some of the principle constraints of microscopic identification are the expertise and time requirements. Identifying pollen via microscopy requires a high level of expertise in the pollen characteristics of the specific plants being studied. With expertise it can still be extremely difficult to
463:
Honeybees carry pollen as well as the nectar used in their production of honey. For food quality and safety concerns it is important to understand the plant providence of human-consumed bee products including honey, royal jelly, and pollen pellets. Investigators can test which plants honeybees
372:
process of DNA can mean that even small pieces of plant DNA can be detected included those from contaminants to a sample. Strict procedures to prevent contamination are important and can be facilitated by the hardiness of the pollen coat allowing the pollen to be washed of contaminants without
389:
Innovations in automated microscopy and imagining software offer one potential alternative in the identification of pollen. Through the use of pattern-recognition software, researchers have developed software that can characterize microscopic pollen images based on texture analyzes.
376:
DNA barcode reference libraries are still being built and standardized target regions are being gradually adopted. These challenges are likely due to the newness of DNA barcoding and will likely improve with the wider adoption of DNA barcoding as a tool used by taxonomists.
68:
involves the specific targeting of gene regions that are found in most to all plant species but have high variation between members of different species. The unique sequence of base pairs for each species within these target regions can be used as an identifying feature.
454:
Due to the hardy structure of pollen which has evolved to survive being transported sometimes great distances while keeping the internal genetic information intact, the origin of pollen found mixed in ancient substrates can often be determined through DNA barcoding.
1067:
Marcos, J. VĂctor; Nava, Rodrigo; CristĂłbal, Gabriel; Redondo, Rafael; Escalante-RamĂrez, Boris; Bueno, Gloria; DĂ©niz, Ă“scar; González-Porto, Amelia; Pardo, Cristina (2015). "Automated pollen identification using microscopic imaging and texture analysis".
441:
Being accurately able to identify pollen found on evidence helps forensic investigators identify which regions evidence originated from based on the plants that are endemic to those regions. In addition to this, atmospheric pollen originating from illegal
1404:
Galliot, Jean-Noël; Brunel, Dominique; Bérard, Aurélie; Chauveau, Aurélie; Blanchetête, André; Lanore, Laurent; Farruggia, Anne (2017-12-01). "Investigating a flower-insect forager network in a mountain grassland community using pollen DNA barcoding".
2065:
Aboulaich, Nadia; Trigo, M. Mar; Bouziane, Hassan; Cabezudo, Baltasar; Recio, Marta; Kadiri, Mohamed El; Ater, Mohammed (2013). "Variations and origin of the atmospheric pollen of
Cannabis detected in the province of Tetouan (NW Morocco): 2008–2010".
1805:
Weiner, Christiane
Natalie; Werner, Michael; Linsenmair, Karl Eduard; Blüthgen, Nico (2014-02-01). "Land-use impacts on plant–pollinator networks: interaction strength and specialization predict pollinator declines".
84:. Each of these fields benefits from the creation of plant barcode reference libraries. These libraries range largely in size and scope of their collections as well as what target region(s) they specialize in.
380:
Determining the amount of each contributor to a mixed pollen load can be difficult to determine through the use of DNA barcoding. However, scientists have been able to compare pollen amounts via rank order.
1121:
Hollingsworth, Peter M.; Forrest, Laura L.; Spouge, John L.; Hajibabaei, Mehrdad; Ratnasingham, Sujeevan; van der Bank, Michelle; Chase, Mark W.; Cowan, Robyn S.; Erickson, David L. (2009-08-04).
1239:
Wang, Xin-Cun; Liu, Chang; Huang, Liang; Bengtsson-Palme, Johan; Chen, Haimei; Zhang, Jian-Hui; Cai, Dayong; Li, Jian-Qin (May 2015). "ITS1: a DNA barcode better than ITS2 in eukaryotes?".
1762:
Matsuki, Yu; Tateno, Ryunosuke; Shibata, Mitsue; Isagi, Yuji (2008-08-01). "Pollination efficiencies of flower-visiting insects as determined by direct genetic analysis of pollen origin".
894:
Wilson, Erin E.; Sidhu, C. Sheena; LeVan, Katherine E.; Holway, David A. (November 2010). "Pollen foraging behaviour of solitary
Hawaiian bees revealed through molecular pollen analysis".
360:
Rare plants visited by some pollinators can be difficult to determine, by using pollen DNA barcoding researchers can uncover "invisible" interactions between plants and pollinators.
91:
is the process of identifying the individual species DNA from a mixed DNA sample and is commonly used to catalog pollen in mixed pollen loads found on pollinating animals and in
615:
Cristescu, Melania E. (2014). "From barcoding single individuals to metabarcoding biological communities: towards an integrative approach to the study of global biodiversity".
429:
can understand the stability of a pollination network and identify which species are most important and which are at most risk to perturbation leading to pollinator declines.
1290:
Pornon, André; Escaravage, Nathalie; Burrus, Monique; Holota, Hélène; Khimoun, Aurélie; Mariette, Jérome; Pellizzari, Charlène; Iribar, Amaia; Etienne, Roselyne (2016).
760:
Sickel, Wiebke; Ankenbrand, Markus J.; Grimmer, Gudrun; Holzschuh, Andrea; Härtel, Stephan; Lanzen, Jonathan; Steffan-Dewenter, Ingolf; Keller, Alexander (2015-07-22).
2109:
Galimberti, Andrea; Mattia, Fabrizio De; Bruni, Ilaria; Scaccabarozzi, Daniela; Sandionigi, Anna; Barbuto, Michela; Casiraghi, Maurizio; Labra, Massimo (2014-10-08).
1704:"Why flower visitation is a poor proxy for pollination: measuring single-visit pollen deposition, with implications for pollination networks and conservation"
1906:
Scheper, Jeroen; Reemer, Menno; van Kats, Ruud; Ozinga, Wim A.; van der Linden, Giel T. J.; Schaminée, Joop H. J.; Siepel, Henk; Kleijn, David (2014-12-09).
446:
farms were successfully detected by scientists which in the future could allow law enforcement officials to narrow down the search areas for illegal farms.
2030:
Miller Coyle, H.; Ladd, C.; Palmbach, T.; Lee, H. C. (June 2001). "The Green
Revolution: botanical contributions to forensics and drug enforcement".
1355:
Bell, Karen L.; Fowler, Julie; Burgess, Kevin S.; Dobbs, Emily K.; Gruenewald, David; Lawley, Brice; Morozumi, Connor; Brosi, Berry J. (2017-06-01).
335:
171:
1456:
Tang, Min; Hardman, Chloe J.; Ji, Yinqiu; Meng, Guanliang; Liu, Shanlin; Tan, Meihua; Yang, Shenzhou; Moss, Ellen D.; Wang, Jiaxin (2015-09-01).
1859:"Forecasting pollination declines through DNA barcoding: the potential contributions of macroecological and macroevolutionary scales of inquiry"
57:. Being able to accurately identify pollen has a wide range of applications though it has been difficult in the past due to the limitations of
504:
Bell, Karen L.; de Vere, Natasha; Keller, Alexander; Richardson, Rodney T.; Gous, Annemarie; Burgess, Kevin S.; Brosi, Berry J. (2016-04-13).
202:
289:
1703:
1647:"Constructing more informative plant–pollinator networks: visitation and pollen deposition networks in a heathland plant community"
284:
279:
658:
Adamowicz, Sarah J.; Steinke, Dirk (2015-11-10). "Increasing global participation in genetics research through DNA barcoding".
1966:
87:
One of the main challenges of identifying pollen is that it is often collected as a mixture of pollen from several species.
1018:
Richardson, Rodney T.; Lin, Chia-Hua; Quijia, Juan O.; Riusech, Natalia S.; Goodell, Karen; Johnson, Reed M. (2015-10-30).
1172:
Pang, Xiaohui; Liu, Chang; Shi, Linchun; Liu, Rui; Liang, Dong; Li, Huan; Cherny, Stacey S.; Chen, Shilin (2012-11-14).
2187:
1020:"Rank-Based Characterization of Pollen Assemblages Collected by Honey Bees Using a Multi-Locus Metabarcoding Approach"
273:
829:"Floral traits influence pollen vectors' choices in higher elevation communities in the Himalaya-Hengduan Mountains"
827:
Zhao, Yan-Hui; Ren, Zong-Xin; Lázaro, Amparo; Wang, Hong; Bernhardt, Peter; Li, Hai-Dong; Li, De-Zhu (2016-05-24).
259:
369:
328:
243:
46:
1580:"The marker choice: Unexpected resolving power of an unexplored CO1 region for layered DNA barcoding approaches"
1174:"Utility of the trnH–psbA Intergenic Spacer Region and Its Combinations as Plant DNA Barcodes: A Meta-Analysis"
1908:"Museum specimens reveal loss of pollen host plants as key factor driving wild bee decline in The Netherlands"
2182:
1578:
Rach, Jessica; Bergmann, Tjard; Paknia, Omid; DeSalle, Rob; Schierwater, Bernd; Hadrys, Heike (2017-04-13).
148:
2197:
762:"Increased efficiency in identifying mixed pollen samples by meta-barcoding with a dual-indexing approach"
321:
308:
95:(also called eDNA) which is DNA extracted straight from the environment such as in soil or water samples.
464:
foraged on and thus the origin of the nectar used in honey by collecting pollen packets from honeybees'
426:
568:"An rbcL Reference Library to Aid in the Identification of Plant Species Mixtures by DNA Metabarcoding"
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1967:"Plant-Pollinator Interactions over 120 Years: Loss of Species, Co-Occurrence, and Function"
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Hebert, Paul D. N.; Cywinska, Alina; Ball, Shelley L.; deWaard, Jeremy R. (2003-02-07).
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Pornon, André; Andalo, Christophe; Burrus, Monique; Escaravage, Nathalie (2017-12-04).
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50:
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Vamosi, Jana C.; Gong, Yan-Bing; Adamowicz, Sarah J.; Packer, Laurence (April 2017).
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33:
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2016:
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1458:"High-throughput monitoring of wild bee diversity and abundance via mitogenomics"
1357:"Applying Pollen DNA Metabarcoding to the Study of Plant–Pollinator Interactions"
1198:
1081:
713:"Trends in Next-Generation Sequencing and a New Era for Whole Genome Sequencing"
77:
978:
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19:
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There are many challenges when it comes to genetic barcoding of pollen. The
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2008:
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1292:"Using metabarcoding to reveal and quantify plant-pollinator interactions"
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2111:"A DNA Barcoding Approach to Characterize Pollen Collected by Honeybees"
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Ballantyne, G.; Baldock, Katherine C. R.; Willmer, P. G. (2015-09-07).
1875:
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Being able to identify pollen is especially important in the study of
566:
Bell, Karen L.; Loeffler, Virginia M.; Brosi, Berry J. (2017-03-01).
38:
1965:
Burkle, Laura A.; Marlin, John C.; Knight, Tiffany M. (2013-03-29).
411:
Butterfly foraging for nectar from a flower in the
Chinese Himalayas
406:
42:
18:
1702:
King, Caroline; Ballantyne, Gavin; Willmer, Pat G. (2013-09-01).
1527:
Proceedings of the Royal
Society of London B: Biological Sciences
506:"Pollen DNA barcoding: current applications and future prospects"
955:"DNA metabarcoding data unveils invisible pollination networks"
54:
399:
ITS1 is better for differentiating species within a genus.
357:
specimens and is then added to a pollen reference library.
72:
The applications of pollen DNA barcoding range from
1523:"Biological identifications through DNA barcodes"
16:Process of identifying pollen donor plant species
1912:Proceedings of the National Academy of Sciences
1127:Proceedings of the National Academy of Sciences
711:Park, Sang Tae; Kim, Jayoung (November 2016).
433:warming, land use change, and other factors.
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53:of specific, conserved regions of plant
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110:
349:identify pollen accurately with high
7:
717:International Neurourology Journal
373:damaging the internal pollen DNA.
290:Consortium for the Barcode of Life
14:
617:Trends in Ecology & Evolution
2068:Science of the Total Environment
1711:Methods in Ecology and Evolution
1462:Methods in Ecology and Evolution
916:10.1111/j.1365-294X.2010.04849.x
303:
302:
118:
2088:10.1016/j.scitotenv.2012.10.075
1123:"A DNA barcode for land plants"
1407:Journal of Insect Conservation
1361:Applications in Plant Sciences
1024:Applications in Plant Sciences
572:Applications in Plant Sciences
37:is the process of identifying
1:
2136:10.1371/journal.pone.0109363
1605:10.1371/journal.pone.0174842
1199:10.1371/journal.pone.0048833
1082:10.1016/j.micron.2014.09.002
468:and identify the pollen via
1241:Molecular Ecology Resources
416:Use in pollination networks
2214:
1764:American Journal of Botany
979:10.1038/s41598-017-16785-5
637:10.1016/j.tree.2014.08.001
260:High throughput sequencing
61:identification of pollen.
1427:10.1007/s10841-017-0022-z
854:10.1186/s12898-016-0080-1
787:10.1186/s12898-015-0051-y
2032:Croatian Medical Journal
197:Environmental DNA (eDNA)
64:Pollen identified using
1992:10.1126/science.1232728
1933:10.1073/pnas.1412973111
1732:10.1111/2041-210x.12074
1482:10.1111/2041-210x.12416
1253:10.1111/1755-0998.12325
1140:10.1073/pnas.0905845106
729:10.5213/inj.1632742.371
1663:10.1098/rspb.2015.1130
1539:10.1098/rspb.2002.2218
412:
28:
672:10.1139/gen-2015-0130
523:10.1139/gen-2015-0200
410:
23:Microscopic image of
22:
1373:10.3732/apps.1600124
1036:10.3732/apps.1500043
584:10.3732/apps.1600110
422:pollination networks
351:taxonomic resolution
45:species through the
2127:2014PLoSO...9j9363G
2080:2013ScTEn.443..413A
1983:2013Sci...339.1611B
1977:(6127): 1611–1615.
1924:2014PNAS..11117552S
1918:(49): 17552–17557.
1863:The New Phytologist
1820:2014Ecol...95..466W
1776:10.3732/ajb.0800036
1723:2013MEcEv...4..811K
1596:2017PLoSO..1274842R
1474:2015MEcEv...6.1034T
1419:2017JICon..21..827G
1308:2016NatSR...627282P
1190:2012PLoSO...748833P
1133:(31): 12794–12797.
971:2017NatSR...716828P
908:2010MolEc..19.4823W
845:2016BMCE...16...26Z
778:2015BMCE...15...20S
723:(Suppl 2): S76–83.
629:2014TEcoE..29..566C
230:Metatranscriptomics
106:Part of a series on
2188:Molecular genetics
1657:(1814): 20151130.
1296:Scientific Reports
959:Scientific Reports
413:
255:Shotgun sequencing
172:macroinvertebrates
29:
1876:10.1111/nph.14356
1828:10.1890/13-0436.1
1533:(1512): 313–321.
1316:10.1038/srep27282
902:(21): 4823–4829.
896:Molecular Ecology
470:DNA metabarcoding
346:
345:
269:Extracellular RNA
203:environmental RNA
93:environmental DNA
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1468:(9): 1034–1043.
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1413:(5–6): 827–837.
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1030:(11): 1500043.
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1247:(3): 573–586.
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578:(3): 1600110.
555:
516:(9): 629–640.
492:
491:
489:
486:
485:
484:
477:
474:
460:
457:
451:
450:Ancient pollen
448:
438:
435:
417:
414:
404:
401:
395:
394:Target regions
392:
386:
383:
365:
362:
344:
343:
341:
340:
333:
326:
318:
315:
314:
313:
312:
296:
295:
293:
292:
287:
282:
277:
271:
265:
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257:
251:
249:
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246:
235:
233:
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226:
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222:
221:
210:
208:
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193:
190:
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185:
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182:
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180:
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174:
166:
161:
156:
151:
145:
142:
141:
137:
136:
123:
115:
114:
108:
107:
100:
97:
15:
13:
10:
9:
6:
4:
3:
2:
2210:
2199:
2198:DNA barcoding
2196:
2194:
2191:
2189:
2186:
2184:
2181:
2180:
2178:
2164:
2160:
2155:
2150:
2146:
2142:
2137:
2132:
2128:
2124:
2120:
2116:
2112:
2105:
2102:
2097:
2093:
2089:
2085:
2081:
2077:
2073:
2069:
2061:
2058:
2053:
2049:
2045:
2041:
2037:
2033:
2026:
2023:
2018:
2014:
2010:
2006:
2002:
1998:
1993:
1988:
1984:
1980:
1976:
1972:
1968:
1961:
1958:
1953:
1949:
1944:
1939:
1934:
1929:
1925:
1921:
1917:
1913:
1909:
1902:
1899:
1894:
1890:
1886:
1882:
1877:
1872:
1868:
1864:
1860:
1853:
1850:
1845:
1841:
1837:
1833:
1829:
1825:
1821:
1817:
1813:
1809:
1801:
1798:
1793:
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1733:
1728:
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1698:
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1690:
1686:
1681:
1676:
1672:
1668:
1664:
1660:
1656:
1652:
1648:
1641:
1638:
1633:
1629:
1624:
1619:
1615:
1611:
1606:
1601:
1597:
1593:
1589:
1585:
1581:
1574:
1571:
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1557:
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1536:
1532:
1528:
1524:
1517:
1514:
1509:
1505:
1500:
1495:
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1487:
1483:
1479:
1475:
1471:
1467:
1463:
1459:
1452:
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1440:
1436:
1432:
1428:
1424:
1420:
1416:
1412:
1408:
1400:
1397:
1392:
1388:
1383:
1378:
1374:
1370:
1366:
1362:
1358:
1351:
1348:
1343:
1339:
1334:
1329:
1325:
1321:
1317:
1313:
1309:
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1301:
1297:
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1278:
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1254:
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1232:
1227:
1223:
1218:
1213:
1209:
1205:
1200:
1195:
1191:
1187:
1183:
1179:
1175:
1168:
1165:
1160:
1156:
1151:
1146:
1141:
1136:
1132:
1128:
1124:
1117:
1114:
1109:
1105:
1101:
1097:
1092:
1087:
1083:
1079:
1075:
1071:
1063:
1060:
1055:
1051:
1046:
1041:
1037:
1033:
1029:
1025:
1021:
1014:
1011:
1006:
1002:
997:
992:
988:
984:
980:
976:
972:
968:
964:
960:
956:
949:
946:
941:
937:
933:
929:
925:
921:
917:
913:
909:
905:
901:
897:
890:
887:
882:
878:
873:
868:
864:
860:
855:
850:
846:
842:
838:
834:
830:
823:
820:
815:
811:
806:
801:
797:
793:
788:
783:
779:
775:
771:
767:
763:
756:
753:
748:
744:
739:
734:
730:
726:
722:
718:
714:
707:
704:
699:
695:
691:
687:
682:
677:
673:
669:
665:
661:
654:
651:
646:
642:
638:
634:
630:
626:
622:
618:
611:
608:
603:
599:
594:
589:
585:
581:
577:
573:
569:
562:
560:
556:
551:
547:
543:
539:
534:
529:
524:
519:
515:
511:
507:
500:
498:
494:
487:
483:
480:
479:
475:
473:
471:
467:
458:
456:
449:
447:
445:
436:
434:
430:
428:
423:
415:
409:
402:
400:
393:
391:
384:
382:
378:
374:
371:
370:amplification
363:
361:
358:
356:
352:
339:
334:
332:
327:
325:
320:
319:
317:
316:
310:
300:
299:
298:
297:
291:
288:
286:
283:
281:
278:
275:
272:
270:
267:
266:
261:
258:
256:
253:
252:
245:
242:
241:
240:
239:Amplification
237:
236:
231:
228:
227:
220:
217:
216:
215:
212:
211:
204:
201:
200:
198:
195:
194:
192:
191:
186:
178:
175:
173:
170:
169:
167:
165:
162:
160:
157:
155:
152:
150:
147:
146:
144:
143:
138:
132:
131:Metabarcoding
128:
127:DNA barcoding
121:
117:
116:
113:
112:DNA barcoding
109:
105:
104:
98:
96:
94:
90:
89:Metabarcoding
85:
83:
79:
75:
70:
67:
66:DNA barcoding
62:
60:
56:
52:
48:
47:amplification
44:
40:
36:
35:
34:DNA barcoding
26:
21:
2118:
2114:
2104:
2071:
2067:
2060:
2035:
2031:
2025:
1974:
1970:
1960:
1915:
1911:
1901:
1869:(1): 11–18.
1866:
1862:
1852:
1811:
1807:
1800:
1767:
1763:
1757:
1714:
1710:
1697:
1654:
1650:
1640:
1587:
1583:
1573:
1530:
1526:
1516:
1465:
1461:
1451:
1410:
1406:
1399:
1364:
1360:
1350:
1302:(1): 27282.
1299:
1295:
1285:
1244:
1240:
1234:
1181:
1177:
1167:
1130:
1126:
1116:
1091:10261/102259
1073:
1069:
1062:
1027:
1023:
1013:
965:(1): 16828.
962:
958:
948:
899:
895:
889:
836:
832:
822:
769:
765:
755:
720:
716:
706:
663:
659:
653:
620:
616:
610:
575:
571:
513:
509:
482:Aeroplankton
462:
453:
440:
431:
419:
403:Applications
397:
388:
385:Alternatives
379:
375:
367:
359:
347:
214:Metagenomics
158:
86:
82:conservation
71:
63:
31:
30:
24:
2074:: 413–419.
833:BMC Ecology
766:BMC Ecology
459:Food safety
78:food safety
59:microscopic
2193:Palynology
2177:Categories
1741:10023/5299
681:1807/70679
533:1807/72815
488:References
364:Challenges
280:Healthcare
99:Advantages
51:sequencing
2145:1932-6203
2044:0353-9504
2001:0036-8075
1885:1469-8137
1836:1939-9170
1784:0002-9122
1749:2041-210X
1671:0962-8452
1614:1932-6203
1547:0962-8452
1490:2041-210X
1435:1366-638X
1324:2045-2322
1261:1755-0998
1208:1932-6203
1076:: 36–46.
987:2045-2322
924:1365-294X
863:1472-6785
839:(1): 26.
796:1472-6785
772:(1): 20.
690:0831-2796
542:0831-2796
437:Forensics
355:herbarium
149:Microbial
74:forensics
25:Ligularia
2163:25296114
2115:PLOS ONE
2096:23208276
2052:11387649
2017:14660808
2009:23449999
1952:25422416
1893:27901268
1844:24669739
1792:21632415
1689:26336181
1632:28406914
1584:PLOS ONE
1565:12614582
1508:27867467
1443:21815003
1391:28690929
1342:27255732
1277:41941842
1269:25187125
1226:23155412
1178:PLOS ONE
1159:19666622
1100:25259684
1054:26649264
1005:29203872
932:20958818
881:27221235
814:26194794
747:27915479
698:26642251
645:25175416
602:28337390
550:27322652
476:See also
444:cannabis
309:Category
168:Aquatic
2154:4190116
2123:Bibcode
2076:Bibcode
1979:Bibcode
1971:Science
1943:4267333
1920:Bibcode
1816:Bibcode
1808:Ecology
1719:Bibcode
1680:4571695
1623:5390999
1592:Bibcode
1556:1691236
1499:5111398
1470:Bibcode
1415:Bibcode
1382:5499302
1333:4891682
1304:Bibcode
1217:3498263
1186:Bibcode
1150:2722355
1108:4520313
1045:4651628
996:5715002
967:Bibcode
940:1862758
904:Bibcode
872:4879733
841:Bibcode
805:4509727
774:Bibcode
738:5169091
625:Bibcode
593:5357121
274:Chimera
219:viruses
140:By taxa
124:
32:Pollen
2161:
2151:
2143:
2094:
2050:
2042:
2015:
2007:
1999:
1950:
1940:
1891:
1883:
1842:
1834:
1790:
1782:
1747:
1687:
1677:
1669:
1630:
1620:
1612:
1563:
1553:
1545:
1506:
1496:
1488:
1441:
1433:
1389:
1379:
1340:
1330:
1322:
1275:
1267:
1259:
1224:
1214:
1206:
1157:
1147:
1106:
1098:
1070:Micron
1052:
1042:
1003:
993:
985:
938:
930:
922:
879:
869:
861:
812:
802:
794:
745:
735:
696:
688:
660:Genome
643:
600:
590:
548:
540:
510:Genome
307:
159:Pollen
154:Fungal
134:
41:donor
39:pollen
27:pollen
2013:S2CID
1707:(PDF)
1439:S2CID
1273:S2CID
1104:S2CID
936:S2CID
188:Other
164:Algae
80:, to
76:, to
43:plant
2159:PMID
2141:ISSN
2092:PMID
2048:PMID
2040:ISSN
2005:PMID
1997:ISSN
1948:PMID
1889:PMID
1881:ISSN
1840:PMID
1832:ISSN
1788:PMID
1780:ISSN
1745:ISSN
1685:PMID
1667:ISSN
1628:PMID
1610:ISSN
1561:PMID
1543:ISSN
1504:PMID
1486:ISSN
1431:ISSN
1387:PMID
1338:PMID
1320:ISSN
1265:PMID
1257:ISSN
1222:PMID
1204:ISSN
1155:PMID
1096:PMID
1050:PMID
1001:PMID
983:ISSN
928:PMID
920:ISSN
877:PMID
859:ISSN
810:PMID
792:ISSN
743:PMID
694:PMID
686:ISSN
641:PMID
598:PMID
546:PMID
538:ISSN
177:fish
49:and
2149:PMC
2131:doi
2084:doi
2072:443
1987:doi
1975:339
1938:PMC
1928:doi
1916:111
1871:doi
1867:214
1824:doi
1772:doi
1737:hdl
1727:doi
1675:PMC
1659:doi
1655:282
1618:PMC
1600:doi
1551:PMC
1535:doi
1531:270
1494:PMC
1478:doi
1423:doi
1377:PMC
1369:doi
1328:PMC
1312:doi
1249:doi
1212:PMC
1194:doi
1145:PMC
1135:doi
1131:106
1086:hdl
1078:doi
1040:PMC
1032:doi
991:PMC
975:doi
912:doi
867:PMC
849:doi
800:PMC
782:doi
733:PMC
725:doi
676:hdl
668:doi
633:doi
588:PMC
580:doi
528:hdl
518:doi
244:PCR
55:DNA
2179::
2157:.
2147:.
2139:.
2129:.
2117:.
2113:.
2090:.
2082:.
2070:.
2046:.
2036:42
2034:.
2011:.
2003:.
1995:.
1985:.
1973:.
1969:.
1946:.
1936:.
1926:.
1914:.
1910:.
1887:.
1879:.
1865:.
1861:.
1838:.
1830:.
1822:.
1812:95
1810:.
1786:.
1778:.
1768:95
1766:.
1743:.
1735:.
1725:.
1713:.
1709:.
1683:.
1673:.
1665:.
1653:.
1649:.
1626:.
1616:.
1608:.
1598:.
1588:12
1586:.
1582:.
1559:.
1549:.
1541:.
1529:.
1525:.
1502:.
1492:.
1484:.
1476:.
1464:.
1460:.
1437:.
1429:.
1421:.
1411:21
1409:.
1385:.
1375:.
1363:.
1359:.
1336:.
1326:.
1318:.
1310:.
1298:.
1294:.
1271:.
1263:.
1255:.
1245:15
1243:.
1220:.
1210:.
1202:.
1192:.
1180:.
1176:.
1153:.
1143:.
1129:.
1125:.
1102:.
1094:.
1084:.
1074:68
1072:.
1048:.
1038:.
1026:.
1022:.
999:.
989:.
981:.
973:.
961:.
957:.
934:.
926:.
918:.
910:.
900:19
898:.
875:.
865:.
857:.
847:.
837:16
835:.
831:.
808:.
798:.
790:.
780:.
770:15
768:.
764:.
741:.
731:.
721:20
719:.
715:.
692:.
684:.
674:.
664:58
662:.
639:.
631:.
621:29
619:.
596:.
586:.
574:.
570:.
558:^
544:.
536:.
526:.
514:59
512:.
508:.
496:^
472:.
129:•
2165:.
2133::
2125::
2119:9
2098:.
2086::
2078::
2054:.
2019:.
1989::
1981::
1954:.
1930::
1922::
1895:.
1873::
1846:.
1826::
1818::
1794:.
1774::
1751:.
1739::
1729::
1721::
1715:4
1691:.
1661::
1634:.
1602::
1594::
1567:.
1537::
1510:.
1480::
1472::
1466:6
1445:.
1425::
1417::
1393:.
1371::
1365:5
1344:.
1314::
1306::
1300:6
1279:.
1251::
1228:.
1196::
1188::
1182:7
1161:.
1137::
1110:.
1088::
1080::
1056:.
1034::
1028:3
1007:.
977::
969::
963:7
942:.
914::
906::
883:.
851::
843::
816:.
784::
776::
749:.
727::
700:.
678::
670::
647:.
635::
627::
604:.
582::
576:5
552:.
530::
520::
337:e
330:t
323:v
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