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1. The complete sequence and comparative analysis of ape sex chromosomes

Author

Makova, Kateryna D., Pickett, Brandon D., Harris, Robert S., Hartley, Gabrielle A., Cechova, Monika, Pal, Karol, Nurk, Sergey, Yoo, DongAhn, Li, Qiuhui, Hebbar, Prajna, McGrath, Barbara C., Antonacci, Francesca, Aubel, Margaux, Biddanda, Arjun, Borchers, Matthew, Bornberg-Bauer, Erich, Bouffard, Gerard G., Brooks, Shelise Y., Carbone, Lucia, Carrel, Laura, Carroll, Andrew, Chang, Pi-Chuan, Chin, Chen-Shan, Cook, Daniel E., Craig, Sarah J. C., de Gennaro, Luciana, Diekhans, Mark, Dutra, Amalia, Garcia, Gage H., Grady, Patrick G. S., Green, Richard E., Haddad, Diana, Hallast, Pille, Harvey, William T., Hickey, Glenn, Hillis, David A., Hoyt, Savannah J., Jeong, Hyeonsoo, Kamali, Kaivan, Pond, Sergei L. Kosakovsky, LaPolice, Troy M., Lee, Charles, Lewis, Alexandra P., Loh, Yong-Hwee E., Masterson, Patrick, McGarvey, Kelly M., McCoy, Rajiv C., Medvedev, Paul, Miga, Karen H., Munson, Katherine M., Pak, Evgenia, Paten, Benedict, Pinto, Brendan J., Potapova, Tamara, Rhie, Arang, Rocha, Joana L., Ryabov, Fedor, Ryder, Oliver A., Sacco, Samuel, Shafin, Kishwar, Shepelev, Valery A., Slon, Viviane, Solar, Steven J., Storer, Jessica M., Sudmant, Peter H., Sweetalana, Sweeten, Alex, Tassia, Michael G., Thibaud-Nissen, Françoise, Ventura, Mario, Wilson, Melissa A., Young, Alice C., Zeng, Huiqing, Zhang, Xinru, Szpiech, Zachary A., Huber, Christian D., Gerton, Jennifer L., Yi, Soojin V., Schatz, Michael C., Alexandrov, Ivan A., Koren, Sergey, O’Neill, Rachel J., Eichler, Evan E., and Phillippy, Adam M.

Published
2024
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2. Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Author

Hynds, Robert E., Huebner, Ariana, Pearce, David R., Hill, Mark S., Akarca, Ayse U., Moore, David A., Ward, Sophia, Gowers, Kate H. C., Karasaki, Takahiro, Al Bakir, Maise, Wilson, Gareth A., Pich, Oriol, Martínez-Ruiz, Carlos, Hossain, A. S. Md Mukarram, Pearce, Simon P., Sivakumar, Monica, Ben Aissa, Assma, Grönroos, Eva, Chandrasekharan, Deepak, Kolluri, Krishna K., Towns, Rebecca, Wang, Kaiwen, Cook, Daniel E., Bosshard-Carter, Leticia, Naceur-Lombardelli, Cristina, Rowan, Andrew J., Veeriah, Selvaraju, Litchfield, Kevin, Crosbie, Philip A. J., Dive, Caroline, Quezada, Sergio A., Janes, Sam M., Jamal-Hanjani, Mariam, Marafioti, Teresa, McGranahan, Nicholas, and Swanton, Charles

Published
2024
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3. A draft human pangenome reference

Author

Liao, Wen-Wei, Asri, Mobin, Ebler, Jana, Doerr, Daniel, Haukness, Marina, Hickey, Glenn, Lu, Shuangjia, Lucas, Julian K, Monlong, Jean, Abel, Haley J, Buonaiuto, Silvia, Chang, Xian H, Cheng, Haoyu, Chu, Justin, Colonna, Vincenza, Eizenga, Jordan M, Feng, Xiaowen, Fischer, Christian, Fulton, Robert S, Garg, Shilpa, Groza, Cristian, Guarracino, Andrea, Harvey, William T, Heumos, Simon, Howe, Kerstin, Jain, Miten, Lu, Tsung-Yu, Markello, Charles, Martin, Fergal J, Mitchell, Matthew W, Munson, Katherine M, Mwaniki, Moses Njagi, Novak, Adam M, Olsen, Hugh E, Pesout, Trevor, Porubsky, David, Prins, Pjotr, Sibbesen, Jonas A, Sirén, Jouni, Tomlinson, Chad, Villani, Flavia, Vollger, Mitchell R, Antonacci-Fulton, Lucinda L, Baid, Gunjan, Baker, Carl A, Belyaeva, Anastasiya, Billis, Konstantinos, Carroll, Andrew, Chang, Pi-Chuan, Cody, Sarah, Cook, Daniel E, Cook-Deegan, Robert M, Cornejo, Omar E, Diekhans, Mark, Ebert, Peter, Fairley, Susan, Fedrigo, Olivier, Felsenfeld, Adam L, Formenti, Giulio, Frankish, Adam, Gao, Yan, Garrison, Nanibaa’ A, Giron, Carlos Garcia, Green, Richard E, Haggerty, Leanne, Hoekzema, Kendra, Hourlier, Thibaut, Ji, Hanlee P, Kenny, Eimear E, Koenig, Barbara A, Kolesnikov, Alexey, Korbel, Jan O, Kordosky, Jennifer, Koren, Sergey, Lee, HoJoon, Lewis, Alexandra P, Magalhães, Hugo, Marco-Sola, Santiago, Marijon, Pierre, McCartney, Ann, McDaniel, Jennifer, Mountcastle, Jacquelyn, Nattestad, Maria, Nurk, Sergey, Olson, Nathan D, Popejoy, Alice B, Puiu, Daniela, Rautiainen, Mikko, Regier, Allison A, Rhie, Arang, Sacco, Samuel, Sanders, Ashley D, Schneider, Valerie A, Schultz, Baergen I, Shafin, Kishwar, Smith, Michael W, Sofia, Heidi J, Abou Tayoun, Ahmad N, Thibaud-Nissen, Françoise, and Tricomi, Francesca Floriana

Subjects
Biological Sciences, Genetics, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Humans, Diploidy, Genome, Human, Haplotypes, Sequence Analysis, DNA, Genomics, Reference Standards, Cohort Studies, Alleles, Genetic Variation, General Science & Technology
Abstract

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.

Published
2023

4. Gaps and complex structurally variant loci in phased genome assemblies

Author

Porubsky, David, Vollger, Mitchell R, Harvey, William T, Rozanski, Allison N, Ebert, Peter, Hickey, Glenn, Hasenfeld, Patrick, Sanders, Ashley D, Stober, Catherine, Consortium, Human Pangenome Reference, Korbel, Jan O, Paten, Benedict, Marschall, Tobias, Eichler, Evan E, Abel, Haley J, Antonacci-Fulton, Lucinda L, Asri, Mobin, Baid, Gunjan, Baker, Carl A, Belyaeva, Anastasiya, Billis, Konstantinos, Bourque, Guillaume, Buonaiuto, Silvia, Carroll, Andrew, Chaisson, Mark JP, Chang, Pi-Chuan, Chang, Xian H, Cheng, Haoyu, Chu, Justin, Cody, Sarah, Colonna, Vincenza, Cook, Daniel E, Cook-Deegan, Robert M, Cornejo, Omar E, Diekhans, Mark, Doerr, Daniel, Ebler, Jana, Eizenga, Jordan M, Fairley, Susan, Fedrigo, Olivier, Felsenfeld, Adam L, Feng, Xiaowen, Fischer, Christian, Flicek, Paul, Formenti, Giulio, Frankish, Adam, Fulton, Robert S, Gao, Yan, Garg, Shilpa, Garrison, Erik, Garrison, Nanibaa’ A, Giron, Carlos Garcia, Green, Richard E, Groza, Cristian, Guarracino, Andrea, Haggerty, Leanne, Hall, Ira M, Haukness, Marina, Haussler, David, Heumos, Simon, Hoekzema, Kendra, Hourlier, Thibaut, Howe, Kerstin, Jain, Miten, Jarvis, Erich D, Ji, Hanlee P, Kenny, Eimear E, Koenig, Barbara A, Kolesnikov, Alexey, Kordosky, Jennifer, Koren, Sergey, Lee, HoJoon, Lewis, Alexandra P, Li, Heng, Liao, Wen-Wei, Lu, Shuangjia, Lu, Tsung-Yu, Lucas, Julian K, Magalhães, Hugo, Marco-Sola, Santiago, Marijon, Pierre, Markello, Charles, Martin, Fergal J, McCartney, Ann, McDaniel, Jennifer, Miga, Karen H, Mitchell, Matthew W, Monlong, Jean, Mountcastle, Jacquelyn, Munson, Katherine M, Mwaniki, Moses Njagi, Nattestad, Maria, Novak, Adam M, and Nurk, Sergey

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Humans, DNA, Satellite, Polymorphism, Genetic, Haplotypes, Segmental Duplications, Genomic, Sequence Analysis, DNA, Human Pangenome Reference Consortium, Medical and Health Sciences, Bioinformatics
Abstract

There has been tremendous progress in phased genome assembly production by combining long-read data with parental information or linked-read data. Nevertheless, a typical phased genome assembly generated by trio-hifiasm still generates more than 140 gaps. We perform a detailed analysis of gaps, assembly breaks, and misorientations from 182 haploid assemblies obtained from a diversity panel of 77 unique human samples. Although trio-based approaches using HiFi are the current gold standard, chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. Importantly, the majority of assembly gaps cluster near the largest and most identical repeats (including segmental duplications [35.4%], satellite DNA [22.3%], or regions enriched in GA/AT-rich DNA [27.4%]). Consequently, 1513 protein-coding genes overlap assembly gaps in at least one haplotype, and 231 are recurrently disrupted or missing from five or more haplotypes. Furthermore, we estimate that 6-7 Mbp of DNA are misorientated per haplotype irrespective of whether trio-free or trio-based approaches are used. Of these misorientations, 81% correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large segmental duplications. We also identify large-scale alignment discontinuities consistent with 11.9 Mbp of deletions and 161.4 Mbp of insertions per haploid genome. Although 99% of this variation corresponds to satellite DNA, we identify 230 regions of euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Such variable and incompletely assembled regions are important targets for future algorithmic development and pangenome representation.

Published
2023

5. Author Correction: The evolution of lung cancer and impact of subclonal selection in TRACERx

Author

Frankell, Alexander M., Dietzen, Michelle, Al Bakir, Maise, Lim, Emilia L., Karasaki, Takahiro, Ward, Sophia, Veeriah, Selvaraju, Colliver, Emma, Huebner, Ariana, Bunkum, Abigail, Hill, Mark S., Grigoriadis, Kristiana, Moore, David A., Black, James R. M., Liu, Wing Kin, Thol, Kerstin, Pich, Oriol, Watkins, Thomas B. K., Naceur-Lombardelli, Cristina, Cook, Daniel E., Salgado, Roberto, Wilson, Gareth A., Bailey, Chris, Angelova, Mihaela, Bentham, Robert, Martínez-Ruiz, Carlos, Abbosh, Christopher, Nicholson, Andrew G., Le Quesne, John, Biswas, Dhruva, Rosenthal, Rachel, Puttick, Clare, Hessey, Sonya, Lee, Claudia, Prymas, Paulina, Toncheva, Antonia, Smith, Jon, Xing, Wei, Nicod, Jerome, Price, Gillian, Kerr, Keith M., Naidu, Babu, Middleton, Gary, Blyth, Kevin G., Fennell, Dean A., Forster, Martin D., Lee, Siow Ming, Falzon, Mary, Hewish, Madeleine, Shackcloth, Michael J., Lim, Eric, Benafif, Sarah, Russell, Peter, Boleti, Ekaterini, Krebs, Matthew G., Lester, Jason F., Papadatos-Pastos, Dionysis, Ahmad, Tanya, Thakrar, Ricky M., Lawrence, David, Navani, Neal, Janes, Sam M., Dive, Caroline, Blackhall, Fiona H., Summers, Yvonne, Cave, Judith, Marafioti, Teresa, Herrero, Javier, Quezada, Sergio A., Peggs, Karl S., Schwarz, Roland F., Van Loo, Peter, Miedema, Daniël M., Birkbak, Nicolai J., Hiley, Crispin T., Hackshaw, Allan, Zaccaria, Simone, Jamal-Hanjani, Mariam, McGranahan, Nicholas, and Swanton, Charles

Published
2024
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6. Knowledge distillation for fast and accurate DNA sequence correction

Author

Belyaeva, Anastasiya, Shor, Joel, Cook, Daniel E., Shafin, Kishwar, Liu, Daniel, Töpfer, Armin, Wenger, Aaron M., Rowell, William J., Yang, Howard, Kolesnikov, Alexey, McLean, Cory Y., Nattestad, Maria, Carroll, Andrew, and Chang, Pi-Chuan

Subjects
Quantitative Biology - Genomics, Computer Science - Machine Learning
Abstract

Accurate genome sequencing can improve our understanding of biology and the genetic basis of disease. The standard approach for generating DNA sequences from PacBio instruments relies on HMM-based models. Here, we introduce Distilled DeepConsensus - a distilled transformer-encoder model for sequence correction, which improves upon the HMM-based methods with runtime constraints in mind. Distilled DeepConsensus is 1.3x faster and 1.5x smaller than its larger counterpart while improving the yield of high quality reads (Q30) over the HMM-based method by 1.69x (vs. 1.73x for larger model). With improved accuracy of genomic sequences, Distilled DeepConsensus improves downstream applications of genomic sequence analysis such as reducing variant calling errors by 39% (34% for larger model) and improving genome assembly quality by 3.8% (4.2% for larger model). We show that the representations learned by Distilled DeepConsensus are similar between faster and slower models.

Published
2022

7. Antibodies against endogenous retroviruses promote lung cancer immunotherapy

Author

Ng, Kevin W., Boumelha, Jesse, Enfield, Katey S. S., Almagro, Jorge, Cha, Hongui, Pich, Oriol, Karasaki, Takahiro, Moore, David A., Salgado, Roberto, Sivakumar, Monica, Young, George, Molina-Arcas, Miriam, de Carné Trécesson, Sophie, Anastasiou, Panayiotis, Fendler, Annika, Au, Lewis, Shepherd, Scott T. C., Martínez-Ruiz, Carlos, Puttick, Clare, Black, James R. M., Watkins, Thomas B. K., Kim, Hyemin, Shim, Seohee, Faulkner, Nikhil, Attig, Jan, Veeriah, Selvaraju, Magno, Neil, Ward, Sophia, Frankell, Alexander M., Al Bakir, Maise, Lim, Emilia L., Hill, Mark S., Wilson, Gareth A., Cook, Daniel E., Birkbak, Nicolai J., Behrens, Axel, Yousaf, Nadia, Popat, Sanjay, Hackshaw, Allan, Hiley, Crispin T., Litchfield, Kevin, McGranahan, Nicholas, Jamal-Hanjani, Mariam, Larkin, James, Lee, Se-Hoon, Turajlic, Samra, Swanton, Charles, Downward, Julian, and Kassiotis, George

Published
2023
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8. The evolution of non-small cell lung cancer metastases in TRACERx

Author

Al Bakir, Maise, Huebner, Ariana, Martínez-Ruiz, Carlos, Grigoriadis, Kristiana, Watkins, Thomas B. K., Pich, Oriol, Moore, David A., Veeriah, Selvaraju, Ward, Sophia, Laycock, Joanne, Johnson, Diana, Rowan, Andrew, Razaq, Maryam, Akther, Mita, Naceur-Lombardelli, Cristina, Prymas, Paulina, Toncheva, Antonia, Hessey, Sonya, Dietzen, Michelle, Colliver, Emma, Frankell, Alexander M., Bunkum, Abigail, Lim, Emilia L., Karasaki, Takahiro, Abbosh, Christopher, Hiley, Crispin T., Hill, Mark S., Cook, Daniel E., Wilson, Gareth A., Salgado, Roberto, Nye, Emma, Stone, Richard Kevin, Fennell, Dean A., Price, Gillian, Kerr, Keith M., Naidu, Babu, Middleton, Gary, Summers, Yvonne, Lindsay, Colin R., Blackhall, Fiona H., Cave, Judith, Blyth, Kevin G., Nair, Arjun, Ahmed, Asia, Taylor, Magali N., Procter, Alexander James, Falzon, Mary, Lawrence, David, Navani, Neal, Thakrar, Ricky M., Janes, Sam M., Papadatos-Pastos, Dionysis, Forster, Martin D., Lee, Siow Ming, Ahmad, Tanya, Quezada, Sergio A., Peggs, Karl S., Van Loo, Peter, Dive, Caroline, Hackshaw, Allan, Birkbak, Nicolai J., Zaccaria, Simone, Jamal-Hanjani, Mariam, McGranahan, Nicholas, and Swanton, Charles

Published
2023
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9. The evolution of lung cancer and impact of subclonal selection in TRACERx

Author

Frankell, Alexander M., Dietzen, Michelle, Al Bakir, Maise, Lim, Emilia L., Karasaki, Takahiro, Ward, Sophia, Veeriah, Selvaraju, Colliver, Emma, Huebner, Ariana, Bunkum, Abigail, Hill, Mark S., Grigoriadis, Kristiana, Moore, David A., Black, James R. M., Liu, Wing Kin, Thol, Kerstin, Pich, Oriol, Watkins, Thomas B. K., Naceur-Lombardelli, Cristina, Cook, Daniel E., Salgado, Roberto, Wilson, Gareth A., Bailey, Chris, Angelova, Mihaela, Bentham, Robert, Martínez-Ruiz, Carlos, Abbosh, Christopher, Nicholson, Andrew G., Le Quesne, John, Biswas, Dhruva, Rosenthal, Rachel, Puttick, Clare, Hessey, Sonya, Lee, Claudia, Prymas, Paulina, Toncheva, Antonia, Smith, Jon, Xing, Wei, Nicod, Jerome, Price, Gillian, Kerr, Keith M., Naidu, Babu, Middleton, Gary, Blyth, Kevin G., Fennell, Dean A., Forster, Martin D., Lee, Siow Ming, Falzon, Mary, Hewish, Madeleine, Shackcloth, Michael J., Lim, Eric, Benafif, Sarah, Russell, Peter, Boleti, Ekaterini, Krebs, Matthew G., Lester, Jason F., Papadatos-Pastos, Dionysis, Ahmad, Tanya, Thakrar, Ricky M., Lawrence, David, Navani, Neal, Janes, Sam M., Dive, Caroline, Blackhall, Fiona H., Summers, Yvonne, Cave, Judith, Marafioti, Teresa, Herrero, Javier, Quezada, Sergio A., Peggs, Karl S., Schwarz, Roland F., Van Loo, Peter, Miedema, Daniël M., Birkbak, Nicolai J., Hiley, Crispin T., Hackshaw, Allan, Zaccaria, Simone, Jamal-Hanjani, Mariam, McGranahan, Nicholas, and Swanton, Charles

Published
2023
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10. Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA

Author

Abbosh, Christopher, Frankell, Alexander M., Harrison, Thomas, Kisistok, Judit, Garnett, Aaron, Johnson, Laura, Veeriah, Selvaraju, Moreau, Mike, Chesh, Adrian, Chaunzwa, Tafadzwa L., Weiss, Jakob, Schroeder, Morgan R., Ward, Sophia, Grigoriadis, Kristiana, Shahpurwalla, Aamir, Litchfield, Kevin, Puttick, Clare, Biswas, Dhruva, Karasaki, Takahiro, Black, James R. M., Martínez-Ruiz, Carlos, Bakir, Maise Al, Pich, Oriol, Watkins, Thomas B. K., Lim, Emilia L., Huebner, Ariana, Moore, David A., Godin-Heymann, Nadia, L’Hernault, Anne, Bye, Hannah, Odell, Aaron, Roberts, Paula, Gomes, Fabio, Patel, Akshay J., Manzano, Elizabeth, Hiley, Crispin T., Carey, Nicolas, Riley, Joan, Cook, Daniel E., Hodgson, Darren, Stetson, Daniel, Barrett, J. Carl, Kortlever, Roderik M., Evan, Gerard I., Hackshaw, Allan, Daber, Robert D., Shaw, Jacqui A., Aerts, Hugo J. W. L., Licon, Abel, Stahl, Josh, Jamal-Hanjani, Mariam, Birkbak, Nicolai J., McGranahan, Nicholas, and Swanton, Charles

Published
2023
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11. Genomic–transcriptomic evolution in lung cancer and metastasis

Author

Martínez-Ruiz, Carlos, Black, James R. M., Puttick, Clare, Hill, Mark S., Demeulemeester, Jonas, Larose Cadieux, Elizabeth, Thol, Kerstin, Jones, Thomas P., Veeriah, Selvaraju, Naceur-Lombardelli, Cristina, Toncheva, Antonia, Prymas, Paulina, Rowan, Andrew, Ward, Sophia, Cubitt, Laura, Athanasopoulou, Foteini, Pich, Oriol, Karasaki, Takahiro, Moore, David A., Salgado, Roberto, Colliver, Emma, Castignani, Carla, Dietzen, Michelle, Huebner, Ariana, Al Bakir, Maise, Tanić, Miljana, Watkins, Thomas B. K., Lim, Emilia L., Al-Rashed, Ali M., Lang, Danny, Clements, James, Cook, Daniel E., Rosenthal, Rachel, Wilson, Gareth A., Frankell, Alexander M., de Carné Trécesson, Sophie, East, Philip, Kanu, Nnennaya, Litchfield, Kevin, Birkbak, Nicolai J., Hackshaw, Allan, Beck, Stephan, Van Loo, Peter, Jamal-Hanjani, Mariam, Swanton, Charles, and McGranahan, Nicholas

Published
2023
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13. Pan-conserved segment tags identify ultra-conserved sequences across assemblies in the human pangenome

Author

Liao, Wen-Wei, Asri, Mobin, Ebler, Jana, Doerr, Daniel, Haukness, Marina, Hickey, Glenn, Lu, Shuangjia, Lucas, Julian K., Monlong, Jean, Abel, Haley J., Buonaiuto, Silvia, Chang, Xian H., Cheng, Haoyu, Chu, Justin, Colonna, Vincenza, Eizenga, Jordan M., Feng, Xiaowen, Fischer, Christian, Fulton, Robert S., Garg, Shilpa, Groza, Cristian, Guarracino, Andrea, Harvey, William T., Heumos, Simon, Howe, Kerstin, Jain, Miten, Lu, Tsung-Yu, Markello, Charles, Martin, Fergal J., Mitchell, Matthew W., Munson, Katherine M., Mwaniki, Moses Njagi, Novak, Adam M., Olsen, Hugh E., Pesout, Trevor, Porubsky, David, Prins, Pjotr, Sibbesen, Jonas A., Tomlinson, Chad, Villani, Flavia, Vollger, Mitchell R., Antonacci-Fulton, Lucinda L., Baid, Gunjan, Baker, Carl A., Belyaeva, Anastasiya, Billis, Konstantinos, Carroll, Andrew, Chang, Pi-Chuan, Cody, Sarah, Cook, Daniel E., Cornejo, Omar E., Diekhans, Mark, Ebert, Peter, Fairley, Susan, Fedrigo, Olivier, Felsenfeld, Adam L., Formenti, Giulio, Frankish, Adam, Gao, Yan, Giron, Carlos Garcia, Green, Richard E., Haggerty, Leanne, Hoekzema, Kendra, Hourlier, Thibaut, Ji, Hanlee P., Kolesnikov, Alexey, Korbel, Jan O., Kordosky, Jennifer, Lee, HoJoon, Lewis, Alexandra P., Magalhães, Hugo, Marco-Sola, Santiago, Marijon, Pierre, McDaniel, Jennifer, Mountcastle, Jacquelyn, Nattestad, Maria, Olson, Nathan D., Puiu, Daniela, Regier, Allison A., Rhie, Arang, Sacco, Samuel, Sanders, Ashley D., Schneider, Valerie A., Schultz, Baergen I., Shafin, Kishwar, Sirén, Jouni, Smith, Michael W., Sofia, Heidi J., Abou Tayoun, Ahmad N., Thibaud-Nissen, Françoise, Tricomi, Francesca Floriana, Wagner, Justin, Wood, Jonathan M.D., Zimin, Aleksey V., Popejoy, Alice B., Bourque, Guillaume, Chaisson, Mark J.P., Flicek, Paul, Phillippy, Adam M., Zook, Justin M., Eichler, Evan E., Haussler, David, Jarvis, Erich D., Miga, Karen H., Wang, Ting, Garrison, Erik, Marschall, Tobias, Hall, Ira, Li, Heng, Paten, Benedict, Greer, Stephanie U., Pavlichin, Dmitri S., Zhou, Bo, Urban, Alexander E., and Weissman, Tsachy

Published
2023
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14. Shared Genomic Regions Underlie Natural Variation in Diverse Toxin Responses

Author

Evans, Kathryn S, Brady, Shannon C, Bloom, Joshua S, Tanny, Robyn E, Cook, Daniel E, Giuliani, Sarah E, Hippleheuser, Stephen W, Zamanian, Mostafa, and Andersen, Erik C

Subjects
Biological Sciences, Genetics, Biotechnology, Human Genome, Generic health relevance, Alleles, Animals, Caenorhabditis elegans, Chromosome Mapping, Epistasis, Genetic, Genomics, Metals, Heavy, Neurotoxins, Pesticides, Quantitative Trait Loci, C. elegans, QTL, genetic interactions, toxin, pleiotropy, Developmental Biology, Biochemistry and cell biology
Abstract

Phenotypic complexity is caused by the contributions of environmental factors and multiple genetic loci, interacting or acting independently. Studies of yeast and Arabidopsis often find that the majority of natural variation across phenotypes is attributable to independent additive quantitative trait loci (QTL). Detected loci in these organisms explain most of the estimated heritable variation. By contrast, many heritable components underlying phenotypic variation in metazoan models remain undetected. Before the relative impacts of additive and interactive variance components on metazoan phenotypic variation can be dissected, high replication and precise phenotypic measurements are required to obtain sufficient statistical power to detect loci contributing to this missing heritability. Here, we used a panel of 296 recombinant inbred advanced intercross lines of Caenorhabditis elegans and a high-throughput fitness assay to detect loci underlying responses to 16 different toxins, including heavy metals, chemotherapeutic drugs, pesticides, and neuropharmaceuticals. Using linkage mapping, we identified 82 QTL that underlie variation in responses to these toxins, and predicted the relative contributions of additive loci and genetic interactions across various growth parameters. Additionally, we identified three genomic regions that impact responses to multiple classes of toxins. These QTL hotspots could represent common factors impacting toxin responses. We went further to generate near-isogenic lines and chromosome substitution strains, and then experimentally validated these QTL hotspots, implicating additive and interactive loci that underlie toxin-response variation.

Published
2018

15. The Genetic Basis of Natural Variation in Caenorhabditis elegans Telomere Length

Author

Cook, Daniel E, Zdraljevic, Stefan, Tanny, Robyn E, Seo, Beomseok, Riccardi, David D, Noble, Luke M, Rockman, Matthew V, Alkema, Mark J, Braendle, Christian, Kammenga, Jan E, Wang, John, Kruglyak, Leonid, Félix, Marie-Anne, Lee, Junho, and Andersen, Erik C

Subjects
Biological Sciences, Genetics, Human Genome, 1.1 Normal biological development and functioning, Underpinning research, Generic health relevance, Animals, Caenorhabditis elegans, Caenorhabditis elegans Proteins, DNA, Genetic Variation, Genome-Wide Association Study, Longevity, Mutation, Sequence Analysis, DNA, Telomere, Telomere-Binding Proteins, QTL, shelterin, telomere length, whole-genome sequence, Developmental Biology, Biochemistry and cell biology
Abstract

Telomeres are involved in the maintenance of chromosomes and the prevention of genome instability. Despite this central importance, significant variation in telomere length has been observed in a variety of organisms. The genetic determinants of telomere-length variation and their effects on organismal fitness are largely unexplored. Here, we describe natural variation in telomere length across the Caenorhabditis elegans species. We identify a large-effect variant that contributes to differences in telomere length. The variant alters the conserved oligonucleotide/oligosaccharide-binding fold of protection of telomeres 2 (POT-2), a homolog of a human telomere-capping shelterin complex subunit. Mutations within this domain likely reduce the ability of POT-2 to bind telomeric DNA, thereby increasing telomere length. We find that telomere-length variation does not correlate with offspring production or longevity in C. elegans wild isolates, suggesting that naturally long telomeres play a limited role in modifying fitness phenotypes in C. elegans.

Published
2016

16. Revolutionizing Inflammatory Bowel Disease Management: A Comprehensive Narrative Review of Innovative Dietary Strategies and Future Directions

Author

Saeed, Shahzeb, primary, Ekhator, Chukwuyem, additional, Abdelaziz, Ali M, additional, Naveed, Husnain, additional, Karski, Amanda, additional, Cook, Daniel E, additional, Reddy, Shivani M, additional, Affaf, Maryam, additional, Khan, Salman J, additional, Bellegarde, Sophia B, additional, Rehman, Abdur, additional, Hasan, Abdul Haseeb, additional, and Shehryar, Abdullah, additional

Published
2023
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17. Pan-conserved segment tags identify ultra-conserved sequences across assemblies in the human pangenome

Author

Lee, HoJoon, primary, Greer, Stephanie U., additional, Pavlichin, Dmitri S., additional, Zhou, Bo, additional, Urban, Alexander E., additional, Weissman, Tsachy, additional, Ji, Hanlee P., additional, Liao, Wen-Wei, additional, Asri, Mobin, additional, Ebler, Jana, additional, Doerr, Daniel, additional, Haukness, Marina, additional, Hickey, Glenn, additional, Lu, Shuangjia, additional, Lucas, Julian K., additional, Monlong, Jean, additional, Abel, Haley J., additional, Buonaiuto, Silvia, additional, Chang, Xian H., additional, Cheng, Haoyu, additional, Chu, Justin, additional, Colonna, Vincenza, additional, Eizenga, Jordan M., additional, Feng, Xiaowen, additional, Fischer, Christian, additional, Fulton, Robert S., additional, Garg, Shilpa, additional, Groza, Cristian, additional, Guarracino, Andrea, additional, Harvey, William T., additional, Heumos, Simon, additional, Howe, Kerstin, additional, Jain, Miten, additional, Lu, Tsung-Yu, additional, Markello, Charles, additional, Martin, Fergal J., additional, Mitchell, Matthew W., additional, Munson, Katherine M., additional, Mwaniki, Moses Njagi, additional, Novak, Adam M., additional, Olsen, Hugh E., additional, Pesout, Trevor, additional, Porubsky, David, additional, Prins, Pjotr, additional, Sibbesen, Jonas A., additional, Tomlinson, Chad, additional, Villani, Flavia, additional, Vollger, Mitchell R., additional, Antonacci-Fulton, Lucinda L., additional, Baid, Gunjan, additional, Baker, Carl A., additional, Belyaeva, Anastasiya, additional, Billis, Konstantinos, additional, Carroll, Andrew, additional, Chang, Pi-Chuan, additional, Cody, Sarah, additional, Cook, Daniel E., additional, Cornejo, Omar E., additional, Diekhans, Mark, additional, Ebert, Peter, additional, Fairley, Susan, additional, Fedrigo, Olivier, additional, Felsenfeld, Adam L., additional, Formenti, Giulio, additional, Frankish, Adam, additional, Gao, Yan, additional, Giron, Carlos Garcia, additional, Green, Richard E., additional, Haggerty, Leanne, additional, Hoekzema, Kendra, additional, Hourlier, Thibaut, additional, Kolesnikov, Alexey, additional, Korbel, Jan O., additional, Kordosky, Jennifer, additional, Lee, HoJoon, additional, Lewis, Alexandra P., additional, Magalhães, Hugo, additional, Marco-Sola, Santiago, additional, Marijon, Pierre, additional, McDaniel, Jennifer, additional, Mountcastle, Jacquelyn, additional, Nattestad, Maria, additional, Olson, Nathan D., additional, Puiu, Daniela, additional, Regier, Allison A., additional, Rhie, Arang, additional, Sacco, Samuel, additional, Sanders, Ashley D., additional, Schneider, Valerie A., additional, Schultz, Baergen I., additional, Shafin, Kishwar, additional, Sirén, Jouni, additional, Smith, Michael W., additional, Sofia, Heidi J., additional, Abou Tayoun, Ahmad N., additional, Thibaud-Nissen, Françoise, additional, Tricomi, Francesca Floriana, additional, Wagner, Justin, additional, Wood, Jonathan M.D., additional, Zimin, Aleksey V., additional, Popejoy, Alice B., additional, Bourque, Guillaume, additional, Chaisson, Mark J.P., additional, Flicek, Paul, additional, Phillippy, Adam M., additional, Zook, Justin M., additional, Eichler, Evan E., additional, Haussler, David, additional, Jarvis, Erich D., additional, Miga, Karen H., additional, Wang, Ting, additional, Garrison, Erik, additional, Marschall, Tobias, additional, Hall, Ira, additional, Li, Heng, additional, and Paten, Benedict, additional

Published
2023
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20. The evolution of lung cancer and impact of subclonal selection in TRACERx

Author

Frankell, Alexander M, Dietzen, Michelle, Al Bakir, Maise, Lim, Emilia L, Karasaki, Takahiro, Ward, Sophia, Veeriah, Selvaraju, Colliver, Emma, Huebner, Ariana, Bunkum, Abigail, Hill, Mark S, Grigoriadis, Kristiana, Moore, David A, Black, James RM, Liu, Wing Kin, Thol, Kerstin, Pich, Oriol, Watkins, Thomas BK, Naceur-Lombardelli, Cristina, Cook, Daniel E, Salgado, Roberto, Wilson, Gareth A, Bailey, Chris, Angelova, Mihaela, Bentham, Robert, Martinez-Ruiz, Carlos, Abbosh, Christopher, Nicholson, Andrew G, Le Quesne, John, Biswas, Dhruva, Rosenthal, Rachel, Puttick, Clare, Hessey, Sonya, Lee, Claudia, Prymas, Paulina, Toncheva, Antonia, Smith, Jon, Xing, Wei, Nicod, Jerome, Price, Gillian, Kerr, Keith M, Naidu, Babu, Middleton, Gary, Blyth, Kevin G, Fennell, Dean A, Forster, Martin D, Lee, Siow Ming, Falzon, Mary, Hewish, Madeleine, Shackcloth, Michael J, Lim, Eric, Benafif, Sarah, Russell, Peter, Boleti, Ekaterini, Krebs, Matthew G, Lester, Jason F, Papadatos-Pastos, Dionysis, Ahmad, Tanya, Thakrar, Ricky M, Lawrence, David, Navani, Neal, Janes, Sam M, Dive, Caroline, Blackhall, Fiona H, Summers, Yvonne, Cave, Judith, Marafioti, Teresa, Herrero, Javier, Quezada, Sergio A, Peggs, Karl S, Schwarz, Roland F, Van Loo, Peter, Miedema, Daniel M, Birkbak, Nicolai J, Hiley, Crispin T, Hackshaw, Allan, Zaccaria, Simone, Jamal-Hanjani, Mariam, McGranahan, Nicholas, Swanton, Charles, Bajaj, Amrita, Nakas, Apostolos, Sodha-Ramdeen, Azmina, Ang, Keng, Tufail, Mohamad, Chowdhry, Mohammed Fiyaz, Scotland, Molly, Boyles, Rebecca, Rathinam, Sridhar, Wilson, Claire, Marrone, Domenic, Dulloo, Sean, Matharu, Gurdeep, Shaw, Jacqui A, Riley, Joa, Primrose, Lindsay, Cheyne, Heather, Khalil, Mohammed, Richardson, Shirley, Cruickshank, Tracey, Gilbert, Kayleigh, Patel, Akshay J, Osman, Aya, Lacson, Christer, Langman, Gerald, Shackleford, Helen, Djearaman, Madava, Kadiri, Salma, Leek, Angela, Hodgkinson, Jack Davies, Totten, Nicola, Montero, Angeles, Smith, Elaine, Fontaine, Eustace, Granato, Felice, Doran, Helen, Novasio, Juliette, Rammohan, Kendadai, Joseph, Leena, Bishop, Paul, Shah, Rajesh, Moss, Stuart, Joshi, Vijay, Crosbie, Philip, Gomes, Fabio, Brown, Kate, Carter, Mathew, Chaturvedi, Anshuman, Priest, Lynsey, Oliveira, Pedro, Lindsay, Colin R, Clipson, Alexandra, Tugwood, Jonathan, Kerr, Alastair, Rothwell, Dominic G, Kilgour, Elaine, Aerts, Hugo JWL, Kaufmann, Tom L, Szallasi, Zoltan, Kisistok, Judit, Sokac, Mateo, Diossy, Miklos, Demeulemeester, Jonas, Stewart, Aengus, Magness, Alastair, Rowan, Andrew, Karamani, Angeliki, Chain, Benny, Campbell, Brittany B, Castignani, Carla, Weeden, Clare E, Richard, Corentin, Pearce, David R, Karagianni, Despoina, Levi, Dina, Hoxha, Elena, Larose Cadieux, Elizabeth, Nye, Emma, Gronroos, Eva, Galvez-Cancino, Felip, Athanasopoulou, Foteini, Gimeno-Valiente, Francisco, Kassiotis, George, Stavrou, Georgia, Mastrokalos, Gerasimos, Zhai, Haoran L, Lowe, Helen L, Matos, Ignacio, Goldman, Jacki, Reading, James L, Rane, Jayant K, Lam, Jie Min, Hartley, John A, Enfield, Katey SS, Selvaraju, Kayalvizhi, Litchfield, Kevin, Ng, Kevin W, Chen, Kezhong, Dijkstra, Krijn, Thakkar, Krupa, Ensell, Leah, Shah, Mansi, Vasquez, Marcos, Litovchenko, Maria, Werner Sunderland, Mariana, Leung, Michelle, Escudero, Mickael, Tanic, Miljana, Sivakumar, Monica, Kanu, Nnennaya, Chervova, Olga, Lucas, Olivia, Al-Sawaf, Othman, Hobson, Philip, Pawlik, Piotr, Stone, Richard Kevin, Hynds, Robert E, Vendramin, Roberto, Saghafinia, Sadegh, Lopez, Saioa, Gamble, Samuel, Ung, Seng Kuong Anakin, Vanloo, Sharon, Boeing, Stefan, Beck, Stephan, Bola, Supreet Kaur, Denner, Tamara, Mourikis, Thanos P, Spanswick, Victoria, Barbe, Vittorio, Lu, Wei-Ting, Hill, William, Wu, Yin, Naito, Yutaka, Ramsden, Zoe, Veiga, Catarina, Royle, Gary, Collins-Fekete, Charles-Antoine, Fraioli, Francesco, Ashford, Paul, Clark, Tristan, Borg, Elaine, Wilson, James, Procter, Alexander James, Ahmed, Asia, Taylor, Magali N, Nair, Arjun, Patrini, Davide, Martinoni Hoogenboom, Emilie, Monk, Fleur, Holding, James W, Choudhary, Junaid, Bhakhri, Kunal, Scarci, Marco, Hayward, Martin, Panagiotopoulos, Nikolaos, Gorman, Pat, Khiroya, Reena, Stephens, Robert CM, Wong, Yien Ning Sophia, Bandula, Steve, Sharp, Abigail, Smith, Sean, Gower, Nicole, Dhanda, Harjot Kaur, Chan, Kitty, Pilotti, Camilla, Leslie, Rachel, Grapa, Anca, Zhang, Hanyun, AbdulJabbar, Khalid, Pan, Xiaoxi, Yuan, Yinyin, Chuter, David, MacKenzie, Mairead, Chee, Serena, Alzetani, Aiman, Scarlett, Lydia, Richards, Jennifer, Ingram, Papawadee, Austin, Silvia, De Sousa, Paulo, Jordan, Simon, Rice, Alexandra, Raubenheimer, Hilgardt, Bhayani, Harshil, Ambrose, Lyn, Devaraj, Anand, Chavan, Hema, Begum, Sofina, Buderi, Silviu, Kaniu, Daniel, Malima, Mpho, Booth, Sarah, Fernandes, Nadia, Shah, Pratibha, Proli, Chiara, Danson, Sarah, Robinson, Lily, Dick, Craig, Kirk, Alan, Asif, Mo, Bilancia, Rocco, Kostoulas, Nikos, and Thomas, Mathew

Subjects
Lung Neoplasms, Treatment Outcome, DNA Copy Number Variations, Mutagenesis, Carcinoma, Non-Small-Cell Lung, Mutation, Smoking, Humans, Adenocarcinoma of Lung, Neoplasm Recurrence, Local, Phylogeny
Abstract

Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource. ispartof: NATURE vol:616 issue:7957 ispartof: location:England status: Published online

Published
2023

21. Antibodies against endogenous retroviruses promote lung cancer immunotherapy

Author

Ng, Kevin W, Boumelha, Jesse, Enfield, Katey SS, Almagro, Jorge, Cha, Hongui, Pich, Oriol, Karasaki, Takahiro, Moore, David A, Salgado, Roberto, Sivakumar, Monica, Young, George, Molina-Arcas, Miriam, de Carné Trécesson, Sophie, Anastasiou, Panayiotis, Fendler, Annika, Au, Lewis, Shepherd, Scott TC, Martínez-Ruiz, Carlos, Puttick, Clare, Black, James RM, Watkins, Thomas BK, Kim, Hyemin, Shim, Seohee, Faulkner, Nikhil, Attig, Jan, Veeriah, Selvaraju, Magno, Neil, Ward, Sophia, Frankell, Alexander M, Al Bakir, Maise, Lim, Emilia L, Hill, Mark S, Wilson, Gareth A, Cook, Daniel E, Birkbak, Nicolai J, Behrens, Axel, Yousaf, Nadia, Popat, Sanjay, Hackshaw, Allan, Consortium, TRACERx, Consortium, CAPTURE, Hiley, Crispin T, Litchfield, Kevin, McGranahan, Nicholas, Jamal-Hanjani, Mariam, Larkin, James, Lee, Se-Hoon, Turajlic, Samra, Swanton, Charles, Downward, Julian, and Kassiotis, George

Subjects
Model organisms, Lung Neoplasms, Immunology, Gene Expression, Adenocarcinoma of Lung, Infectious Disease, Antibodies, Cohort Studies, Mice, Signalling & Oncogenes, Ecology,Evolution & Ethology, Carcinoma, Non-Small-Cell Lung, Tumor Microenvironment, Animals, Humans, Lung, Computational & Systems Biology, Chemical Biology & High Throughput, B-Lymphocytes, Human Biology & Physiology, Stem Cells, FOS: Clinical medicine, Endogenous Retroviruses, Genome Integrity & Repair, Cell Biology, Tumour Biology, Disease Models, Animal, Cell Cycle & Chromosomes, Immunotherapy, Genetics & Genomics
Abstract

B cells are frequently found in the margins of solid tumours as organized follicles in ectopic lymphoid organs called tertiary lymphoid structures (TLS)1,2. Although TLS have been found to correlate with improved patient survival and response to immune checkpoint blockade (ICB), the underlying mechanisms of this association remain elusive1,2. Here we investigate lung-resident B cell responses in patients from the TRACERx 421 (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy) and other lung cancer cohorts, and in a recently established immunogenic mouse model for lung adenocarcinoma3. We find that both human and mouse lung adenocarcinomas elicit local germinal centre responses and tumour-binding antibodies, and further identify endogenous retrovirus (ERV) envelope glycoproteins as a dominant anti-tumour antibody target. ERV-targeting B cell responses are amplified by ICB in both humans and mice, and by targeted inhibition of KRAS(G12C) in the mouse model. ERV-reactive antibodies exert anti-tumour activity that extends survival in the mouse model, and ERV expression predicts the outcome of ICB in human lung adenocarcinoma. Finally, we find that effective immunotherapy in the mouse model requires CXCL13-dependent TLS formation. Conversely, therapeutic CXCL13 treatment potentiates anti-tumour immunity and synergizes with ICB. Our findings provide a possible mechanistic basis for the association of TLS with immunotherapy response. ispartof: NATURE vol:616 issue:7957 ispartof: location:England status: Published online

Published
2023
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22. DeepConsensus improves the accuracy of sequences with a gap-aware sequence transformer

Author

Baid, Gunjan, primary, Cook, Daniel E., additional, Shafin, Kishwar, additional, Yun, Taedong, additional, Llinares-López, Felipe, additional, Berthet, Quentin, additional, Belyaeva, Anastasiya, additional, Töpfer, Armin, additional, Wenger, Aaron M., additional, Rowell, William J., additional, Yang, Howard, additional, Kolesnikov, Alexey, additional, Ammar, Waleed, additional, Vert, Jean-Philippe, additional, Vaswani, Ashish, additional, McLean, Cory Y., additional, Nattestad, Maria, additional, Chang, Pi-Chuan, additional, and Carroll, Andrew, additional

Published
2022
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23. Balancing selection maintains hyper-divergent haplotypes in C. elegans

Author

Lee, Daehan, Zdraljevic, Stefan, Stevens, Lewis, Wang, Ye, Tanny, Robyn E., Crombie, Timothy A., Cook, Daniel E., Webster, Amy K., Chirakar, Rojin, Baugh, L. Ryan, Sterken, Mark G., Braendle, Christian, Félix, Marie-Anne, Rockman, Matthew V., and Andersen, Erik C.

Subjects
Genome, Haplotypes, Animals, Genetic Variation, Caenorhabditis elegans, Biological Evolution, Article
Abstract

Across diverse taxa, selfing species have evolved independently from outcrossing species thousands of times. The transition from outcrossing to selfing significantly decreases the effective population size, effective recombination rate, and heterozygosity within a species. These changes lead to a reduction in genetic diversity, and therefore adaptive potential, by intensifying the effects of random genetic drift and linked selection. Within the nematode genus Caenorhabditis, selfing has evolved at least three times and all three species, including in the model organism Caenorhabditis elegans, show substantially reduced genetic diversity relative to outcrossing species. Selfing and outcrossing Caenorhabditis species are often found in the same niches, but we still do not know how selfing species with limited genetic diversity can adapt to these environments. Here, we examine the whole-genome sequences from 609 wild C. elegans strains isolated worldwide and show that genetic variation is concentrated in punctuated hyper-divergent regions that cover 20% of the C. elegans reference genome. These regions are enriched in environmental response genes that mediate sensory perception, pathogen response, and xenobiotic stress response. Population genomic evidence suggests that genetic diversity in these regions has been maintained by long-term balancing selection. Using long- read genome assemblies for 15 wild strains, we show that hyper-divergent haplotypes contain unique sets of genes and show levels of divergence comparable to levels found between Caenorhabditis species that diverged millions of years ago. These results provide an example for how species can avoid the evolutionary “dead end” associated with selfing.

Published
2021

26. Deep sampling of Hawaiian Caenorhabditis elegans reveals high genetic diversity and admixture with global populations

Author

Crombie, Tim A, primary, Zdraljevic, Stefan, additional, Cook, Daniel E, additional, Tanny, Robyn E, additional, Brady, Shannon C, additional, Wang, Ye, additional, Evans, Kathryn S, additional, Hahnel, Steffen, additional, Lee, Daehan, additional, Rodriguez, Briana C, additional, Zhang, Gaotian, additional, van der Zwagg, Joost, additional, Kiontke, Karin, additional, and Andersen, Erik C, additional

Published
2019
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27. Population Selection and Sequencing of Caenorhabditis elegans Wild Isolates Identifies a Region on Chromosome III Affecting Starvation Resistance

Author

Webster, Amy K, primary, Hung, Anthony, additional, Moore, Brad T, additional, Guzman, Ryan, additional, Jordan, James M, additional, Kaplan, Rebecca E W, additional, Hibshman, Jonathan D, additional, Tanny, Robyn E, additional, Cook, Daniel E, additional, Andersen, Erik, additional, and Baugh, L Ryan, additional

Published
2019
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30. Natural variation in a single amino acid underlies cellular responses to topoisomerase II poisons

Author

Zdraljevic, Stefan, Strand, Christine, Seidel, Hannah S., Cook, Daniel E., Doench, John G., and Andersen, Erik C.

Subjects
Genetics, Genome instability, medicine.medical_specialty, Methionine, biology, ved/biology, Topoisomerase, ved/biology.organism_classification_rank.species, biology.organism_classification, Glutamine, chemistry.chemical_compound, Biochemistry, chemistry, Molecular genetics, biology.protein, medicine, Model organism, Etoposide, Caenorhabditis elegans, medicine.drug
Abstract

Many medications, including chemotherapeutics, are differentially effective from one patient to the next. Understanding the causes of these population-wide differences is a critical step towards the development of personalized treatments and improvements to existing medications. Here, we investigate natural differences in sensitivity to anti-neoplastic drugs that target topoisomerase II, using the model organismCaenorhabditis elegans. We show that wild isolates ofC. elegansvary in their sensitivity to these drugs, and we use an unbiased statistical and molecular genetics approach to demonstrate that this variation is explained by a methionine-to-glutamine substitution in topoisomerase II (TOP-2). The presence of a non-polar methionine at this residue increases hydrophobic interactions between TOP-2 and the poison etoposide, as compared to a polar glutamine. We hypothesize that this stabilizing interaction results in increased genomic instability in strains that contain a methionine residue. The residue affected by this substitution is conserved from yeast to humans and is one of the few differences between the two human topoisomerase II isoforms (methionine in hTOPIIα and glutamine in hTOPIIβ). We go on to show that this substitution influences binding and cytotoxicity of etoposide and two additional topoisomerase II poisons in human cell lines. These results explain why hTOPIIα and hTOPIIβ are differentially affected by various poisons and demonstrate the utility ofC. elegansin understanding the genetics of drug responses.

Published
2017

35. The Genetic Basis of Natural Variation inCaenorhabditis elegansTelomere Length

Author

Cook, Daniel E, primary, Zdraljevic, Stefan, additional, Tanny, Robyn E, additional, Seo, Beomseok, additional, Riccardi, David D, additional, Noble, Luke M, additional, Rockman, Matthew V, additional, Alkema, Mark J, additional, Braendle, Christian, additional, Kammenga, Jan E, additional, Wang, John, additional, Kruglyak, Leonid, additional, Félix, Marie-Anne, additional, Lee, Junho, additional, and Andersen, Erik C, additional

Published
2016
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36. DYRK1A controls the transition from proliferation to quiescence during lymphoid development by destabilizing Cyclin D3

Author

Thompson, Benjamin J., primary, Bhansali, Rahul, additional, Diebold, Lauren, additional, Cook, Daniel E., additional, Stolzenburg, Lindsay, additional, Casagrande, Anne-Sophie, additional, Besson, Thierry, additional, Leblond, Bertrand, additional, Désiré, Laurent, additional, Malinge, Sébastien, additional, and Crispino, John D., additional

Published
2015
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38. DYRK1A controls the transition from proliferation to quiescence during lymphoid development by destabilizing Cyclin D3

Author

Thompson, Benjamin J., Bhansali, Rahul, Diebold, Lauren, Cook, Daniel E., Stolzenburg, Lindsay, Casagrande, Anne-Sophie, Besson, Thierry, Leblond, Bertrand, Désiré, Laurent, Malinge, Sébastien, and Crispino, John D.

Abstract

Pre–B and pre–T lymphocytes must orchestrate a transition from a highly proliferative state to a quiescent one during development. Cyclin D3 is essential for these cells’ proliferation, but little is known about its posttranslational regulation at this stage. Here, we show that the dual specificity tyrosine-regulated kinase 1A (DYRK1A) restrains Cyclin D3 protein levels by phosphorylating T283 to induce its degradation. Loss of DYRK1A activity, via genetic inactivation or pharmacologic inhibition in mice, caused accumulation of Cyclin D3 protein, incomplete repression of E2F-mediated gene transcription, and failure to properly couple cell cycle exit with differentiation. Expression of a nonphosphorylatable Cyclin D3 T283A mutant recapitulated these defects, whereas inhibition of Cyclin D:CDK4/6 mitigated the effects of DYRK1A inhibition or loss. These data uncover a previously unknown role for DYRK1A in lymphopoiesis, and demonstrate how Cyclin D3 protein stability is negatively regulated during exit from the proliferative phases of B and T cell development.

Published
2015
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39. The distribution of mutational effects on fitness in Caenorhabditis elegansinferred from standing genetic variation

Author

Gilbert, Kimberly J, Zdraljevic, Stefan, Cook, Daniel E, Cutter, Asher D, Andersen, Erik C, and Baer, Charles F

Abstract

The distribution of fitness effects (DFE) for new mutations is one of the most theoretically important but difficult to estimate properties in population genetics. A crucial challenge to inferring the DFE from natural genetic variation is the sensitivity of the site frequency spectrum to factors like population size change, population substructure, genome structure, and nonrandom mating. Although inference methods aim to control for population size changes, the influence of nonrandom mating remains incompletely understood, despite being a common feature of many species. We report the DFE estimated from 326 genomes of Caenorhabditis elegans, a nematode roundworm with a high rate of self-fertilization. We evaluate the robustness of DFE inferences using simulated data that mimics the genomic structure and reproductive life history of C. elegans. Our observations demonstrate how the combined influence of self-fertilization, genome structure, and natural selection on linked sites can conspire to compromise estimates of the DFE from extant polymorphisms with existing methods. These factors together tend to bias inferences toward weakly deleterious mutations, making it challenging to have full confidence in the inferred DFE of new mutations as deduced from standing genetic variation in species like C. elegans. Improved methods for inferring the DFE are needed to appropriately handle strong linked selection and selfing. These results highlight the importance of understanding the combined effects of processes that can bias our interpretations of evolution in natural populations.

Published
2022
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40. The distribution of mutational effects on fitness in Caenorhabditis elegans inferred from standing genetic variation.

Author

Gilbert, Kimberly J., Zdraljevic, Stefan, Cook, Daniel E., Cutter, Asher D., Andersen, Erik C., and Baer, Charles F.

Subjects
*GENETIC mutation, *GENETICS, *CAENORHABDITIS elegans, *ANIMAL experimentation, *STANDING position, *GENETIC variation, *GENOMES
Abstract

The distribution of fitness effects (DFE) for new mutations is one of the most theoretically important but difficult to estimate properties in population genetics. A crucial challenge to inferring the DFE from natural genetic variation is the sensitivity of the site frequency spectrum to factors like population size change, population substructure, genome structure, and nonrandom mating. Although inference methods aim to control for population size changes, the influence of nonrandom mating remains incompletely understood, despite being a common feature of many species. We report the DFE estimated from 326 genomes of Caenorhabditis elegans, a nematode roundworm with a high rate of self-fertilization. We evaluate the robustness of DFE inferences using simulated data that mimics the genomic structure and reproductive life history of C. elegans. Our observations demonstrate how the combined influence of self-fertilization, genome structure, and natural selection on linked sites can conspire to compromise estimates of the DFE from extant polymorphisms with existing methods. These factors together tend to bias inferences toward weakly deleterious mutations, making it challenging to have full confidence in the inferred DFE of new mutations as deduced from standing genetic variation in species like C. elegans. Improved methods for inferring the DFE are needed to appropriately handle strong linked selection and selfing. These results highlight the importance of understanding the combined effects of processes that can bias our interpretations of evolution in natural populations. [ABSTRACT FROM AUTHOR]

Published
2022
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41. Shared Genomic Regions Underlie Natural Variation in Diverse Toxin Responses.

Author

Tanny, Robyn E., Giuliani, Sarah E., Hippleheuser, Stephen W., Evans, Kathryn S., Brady, Shannon C., Cook, Daniel E., Andersen, Erik C., Bloom, Joshua S., and Zamanian, Mostafa

Subjects
*CANCER chemotherapy, *CHROMOSOMES, *GENETIC polymorphisms, *GENOMES, *HEAVY metals, *NEUROSCIENCES, *PESTICIDES, *RECOMBINANT DNA, *TOXINS, *PHENOTYPES, *GENOMICS
Abstract

Phenotypic complexity is caused by the contributions of environmental factors and multiple genetic loci, interacting or acting independently. Studies of yeast and Arabidopsis often find that the majority of natural variation across phenotypes is attributable to independent additive quantitative trait loci (QTL). Detected loci in these organisms explain most of the estimated heritable variation. By contrast, many heritable components underlying phenotypic variation in metazoan models remain undetected. Before the relative impacts of additive and interactive variance components on metazoan phenotypic variation can be dissected, high replication and precise phenotypic measurements are required to obtain sufficient statistical power to detect loci contributing to this missing heritability. Here, we used a panel of 296 recombinant inbred advanced intercross lines of Caenorhabditis elegans and a highthroughput fitness assay to detect loci underlying responses to 16 different toxins, including heavy metals, chemotherapeutic drugs, pesticides, and neuropharmaceuticals. Using linkage mapping, we identified 82 QTL that underlie variation in responses to these toxins, and predicted the relative contributions of additive loci and genetic interactions across various growth parameters. Additionally, we identified three genomic regions that impact responses to multiple classes of toxins. These QTL hotspots could represent common factors impacting toxin responses. We went further to generate near-isogenic lines and chromosome substitution strains, and then experimentally validated these QTL hotspots, implicating additive and interactive loci that underlie toxin-response variation. [ABSTRACT FROM AUTHOR]

Published
2018
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42. A deep-learning-based RNA-seq germline variant caller.

Author

Cook DE, Venkat A, Yelizarov D, Pouliot Y, Chang PC, Carroll A, and De La Vega FM

Abstract

Summary: RNA sequencing (RNA-seq) can be applied to diverse tasks including quantifying gene expression, discovering quantitative trait loci and identifying gene fusion events. Although RNA-seq can detect germline variants, the complexities of variable transcript abundance, target capture and amplification introduce challenging sources of error. Here, we extend DeepVariant, a deep-learning-based variant caller, to learn and account for the unique challenges presented by RNA-seq data. Our DeepVariant RNA-seq model produces highly accurate variant calls from RNA-sequencing data, and outperforms existing approaches such as Platypus and GATK. We examine factors that influence accuracy, how our model addresses RNA editing events and how additional thresholding can be used to facilitate our models' use in a production pipeline., Supplementary Information: Supplementary data are available at Bioinformatics Advances online., (© The Author(s) 2023. Published by Oxford University Press.)

Published
2023
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43. An automated approach to quantify chemotaxis index in C. elegans .

Author

Crombie TA, Chikuturudzi C, Cook DE, and Andersen EC

Abstract

Chemotaxis assays are used extensively to study behavioral responses of Caenorhabditis nematodes to environmental cues. These assays result in a chemotaxis index (CI) that denotes the behavioral response of a population of nematodes to a particular compound and can range from 1 (maximum attraction) to -1 (maximum avoidance). Traditional chemotaxis assays have low throughput because researchers must manually setup experimental populations and score CIs. Here, we describe an automated methodology that increases throughput by using liquid-handling robots to setup experimental populations and a custom image analysis package, ct, to automate the scoring of CIs from plate images., (Copyright: © 2022 by the authors.)

Published
2022
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