Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas
Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the ro...
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| Autor*in: |
Silver, Luke W. [verfasserIn] McLennan, Elspeth A. [verfasserIn] Beaman, Julian [verfasserIn] da Silva, Karen Burke [verfasserIn] Timms, Peter [verfasserIn] Hogg, Carolyn J. [verfasserIn] Belov, Katherine [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2024 |
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| Übergeordnetes Werk: |
Enthalten in: Immunogenetics - Springer Berlin Heidelberg, 1974, 76(2024), 5-6 vom: 05. Okt., Seite 381-395 |
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| Übergeordnetes Werk: |
volume:76 ; year:2024 ; number:5-6 ; day:05 ; month:10 ; pages:381-395 |
| Links: |
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| DOI / URN: |
10.1007/s00251-024-01356-6 |
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| Katalog-ID: |
SPR057959676 |
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| 520 | |a Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. Overall, we have provided a bioinformatic workflow for investigating variation in a complex immune gene family from whole genome sequencing data and determined current levels of diversity within koala MHC genes. | ||
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| 650 | 4 | |a MHC |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Koalas |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a McLennan, Elspeth A. |e verfasserin |0 (orcid)0000-0002-6872-8597 |4 aut | |
| 700 | 1 | |a Beaman, Julian |e verfasserin |0 (orcid)0000-0002-1618-5308 |4 aut | |
| 700 | 1 | |a da Silva, Karen Burke |e verfasserin |0 (orcid)0000-0002-0294-6583 |4 aut | |
| 700 | 1 | |a Timms, Peter |e verfasserin |0 (orcid)0000-0002-1682-0025 |4 aut | |
| 700 | 1 | |a Hogg, Carolyn J. |e verfasserin |0 (orcid)0000-0002-6328-398X |4 aut | |
| 700 | 1 | |a Belov, Katherine |e verfasserin |0 (orcid)0000-0002-9762-5554 |4 aut | |
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10.1007/s00251-024-01356-6 doi (DE-627)SPR057959676 (SPR)s00251-024-01356-6-e DE-627 ger DE-627 rakwb eng 570 VZ 44.45 bkl Silver, Luke W. verfasserin (orcid)0000-0002-1718-5756 aut Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. Overall, we have provided a bioinformatic workflow for investigating variation in a complex immune gene family from whole genome sequencing data and determined current levels of diversity within koala MHC genes. Whole genome resequencing (dpeaa)DE-He213 TLR (dpeaa)DE-He213 Functional genomics (dpeaa)DE-He213 Bioinformatics (dpeaa)DE-He213 MHC (dpeaa)DE-He213 Koalas (dpeaa)DE-He213 McLennan, Elspeth A. verfasserin (orcid)0000-0002-6872-8597 aut Beaman, Julian verfasserin (orcid)0000-0002-1618-5308 aut da Silva, Karen Burke verfasserin (orcid)0000-0002-0294-6583 aut Timms, Peter verfasserin (orcid)0000-0002-1682-0025 aut Hogg, Carolyn J. verfasserin (orcid)0000-0002-6328-398X aut Belov, Katherine verfasserin (orcid)0000-0002-9762-5554 aut Enthalten in Immunogenetics Springer Berlin Heidelberg, 1974 76(2024), 5-6 vom: 05. Okt., Seite 381-395 (DE-627)23550355X (DE-600)1398344-1 1432-1211 nnns volume:76 year:2024 number:5-6 day:05 month:10 pages:381-395 https://dx.doi.org/10.1007/s00251-024-01356-6 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 44.45 VZ AR 76 2024 5-6 05 10 381-395 |
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10.1007/s00251-024-01356-6 doi (DE-627)SPR057959676 (SPR)s00251-024-01356-6-e DE-627 ger DE-627 rakwb eng 570 VZ 44.45 bkl Silver, Luke W. verfasserin (orcid)0000-0002-1718-5756 aut Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. Overall, we have provided a bioinformatic workflow for investigating variation in a complex immune gene family from whole genome sequencing data and determined current levels of diversity within koala MHC genes. Whole genome resequencing (dpeaa)DE-He213 TLR (dpeaa)DE-He213 Functional genomics (dpeaa)DE-He213 Bioinformatics (dpeaa)DE-He213 MHC (dpeaa)DE-He213 Koalas (dpeaa)DE-He213 McLennan, Elspeth A. verfasserin (orcid)0000-0002-6872-8597 aut Beaman, Julian verfasserin (orcid)0000-0002-1618-5308 aut da Silva, Karen Burke verfasserin (orcid)0000-0002-0294-6583 aut Timms, Peter verfasserin (orcid)0000-0002-1682-0025 aut Hogg, Carolyn J. verfasserin (orcid)0000-0002-6328-398X aut Belov, Katherine verfasserin (orcid)0000-0002-9762-5554 aut Enthalten in Immunogenetics Springer Berlin Heidelberg, 1974 76(2024), 5-6 vom: 05. Okt., Seite 381-395 (DE-627)23550355X (DE-600)1398344-1 1432-1211 nnns volume:76 year:2024 number:5-6 day:05 month:10 pages:381-395 https://dx.doi.org/10.1007/s00251-024-01356-6 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 44.45 VZ AR 76 2024 5-6 05 10 381-395 |
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10.1007/s00251-024-01356-6 doi (DE-627)SPR057959676 (SPR)s00251-024-01356-6-e DE-627 ger DE-627 rakwb eng 570 VZ 44.45 bkl Silver, Luke W. verfasserin (orcid)0000-0002-1718-5756 aut Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. Overall, we have provided a bioinformatic workflow for investigating variation in a complex immune gene family from whole genome sequencing data and determined current levels of diversity within koala MHC genes. Whole genome resequencing (dpeaa)DE-He213 TLR (dpeaa)DE-He213 Functional genomics (dpeaa)DE-He213 Bioinformatics (dpeaa)DE-He213 MHC (dpeaa)DE-He213 Koalas (dpeaa)DE-He213 McLennan, Elspeth A. verfasserin (orcid)0000-0002-6872-8597 aut Beaman, Julian verfasserin (orcid)0000-0002-1618-5308 aut da Silva, Karen Burke verfasserin (orcid)0000-0002-0294-6583 aut Timms, Peter verfasserin (orcid)0000-0002-1682-0025 aut Hogg, Carolyn J. verfasserin (orcid)0000-0002-6328-398X aut Belov, Katherine verfasserin (orcid)0000-0002-9762-5554 aut Enthalten in Immunogenetics Springer Berlin Heidelberg, 1974 76(2024), 5-6 vom: 05. Okt., Seite 381-395 (DE-627)23550355X (DE-600)1398344-1 1432-1211 nnns volume:76 year:2024 number:5-6 day:05 month:10 pages:381-395 https://dx.doi.org/10.1007/s00251-024-01356-6 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 44.45 VZ AR 76 2024 5-6 05 10 381-395 |
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10.1007/s00251-024-01356-6 doi (DE-627)SPR057959676 (SPR)s00251-024-01356-6-e DE-627 ger DE-627 rakwb eng 570 VZ 44.45 bkl Silver, Luke W. verfasserin (orcid)0000-0002-1718-5756 aut Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. Overall, we have provided a bioinformatic workflow for investigating variation in a complex immune gene family from whole genome sequencing data and determined current levels of diversity within koala MHC genes. Whole genome resequencing (dpeaa)DE-He213 TLR (dpeaa)DE-He213 Functional genomics (dpeaa)DE-He213 Bioinformatics (dpeaa)DE-He213 MHC (dpeaa)DE-He213 Koalas (dpeaa)DE-He213 McLennan, Elspeth A. verfasserin (orcid)0000-0002-6872-8597 aut Beaman, Julian verfasserin (orcid)0000-0002-1618-5308 aut da Silva, Karen Burke verfasserin (orcid)0000-0002-0294-6583 aut Timms, Peter verfasserin (orcid)0000-0002-1682-0025 aut Hogg, Carolyn J. verfasserin (orcid)0000-0002-6328-398X aut Belov, Katherine verfasserin (orcid)0000-0002-9762-5554 aut Enthalten in Immunogenetics Springer Berlin Heidelberg, 1974 76(2024), 5-6 vom: 05. Okt., Seite 381-395 (DE-627)23550355X (DE-600)1398344-1 1432-1211 nnns volume:76 year:2024 number:5-6 day:05 month:10 pages:381-395 https://dx.doi.org/10.1007/s00251-024-01356-6 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 44.45 VZ AR 76 2024 5-6 05 10 381-395 |
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10.1007/s00251-024-01356-6 doi (DE-627)SPR057959676 (SPR)s00251-024-01356-6-e DE-627 ger DE-627 rakwb eng 570 VZ 44.45 bkl Silver, Luke W. verfasserin (orcid)0000-0002-1718-5756 aut Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. Overall, we have provided a bioinformatic workflow for investigating variation in a complex immune gene family from whole genome sequencing data and determined current levels of diversity within koala MHC genes. Whole genome resequencing (dpeaa)DE-He213 TLR (dpeaa)DE-He213 Functional genomics (dpeaa)DE-He213 Bioinformatics (dpeaa)DE-He213 MHC (dpeaa)DE-He213 Koalas (dpeaa)DE-He213 McLennan, Elspeth A. verfasserin (orcid)0000-0002-6872-8597 aut Beaman, Julian verfasserin (orcid)0000-0002-1618-5308 aut da Silva, Karen Burke verfasserin (orcid)0000-0002-0294-6583 aut Timms, Peter verfasserin (orcid)0000-0002-1682-0025 aut Hogg, Carolyn J. verfasserin (orcid)0000-0002-6328-398X aut Belov, Katherine verfasserin (orcid)0000-0002-9762-5554 aut Enthalten in Immunogenetics Springer Berlin Heidelberg, 1974 76(2024), 5-6 vom: 05. Okt., Seite 381-395 (DE-627)23550355X (DE-600)1398344-1 1432-1211 nnns volume:76 year:2024 number:5-6 day:05 month:10 pages:381-395 https://dx.doi.org/10.1007/s00251-024-01356-6 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2574 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 44.45 VZ AR 76 2024 5-6 05 10 381-395 |
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Enthalten in Immunogenetics 76(2024), 5-6 vom: 05. Okt., Seite 381-395 volume:76 year:2024 number:5-6 day:05 month:10 pages:381-395 |
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Whole genome resequencing TLR Functional genomics Bioinformatics MHC Koalas |
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Immunogenetics |
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Silver, Luke W. @@aut@@ McLennan, Elspeth A. @@aut@@ Beaman, Julian @@aut@@ da Silva, Karen Burke @@aut@@ Timms, Peter @@aut@@ Hogg, Carolyn J. @@aut@@ Belov, Katherine @@aut@@ |
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Silver, Luke W. |
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Silver, Luke W. ddc 570 bkl 44.45 misc Whole genome resequencing misc TLR misc Functional genomics misc Bioinformatics misc MHC misc Koalas Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas |
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570 VZ 44.45 bkl Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas Whole genome resequencing (dpeaa)DE-He213 TLR (dpeaa)DE-He213 Functional genomics (dpeaa)DE-He213 Bioinformatics (dpeaa)DE-He213 MHC (dpeaa)DE-He213 Koalas (dpeaa)DE-He213 |
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Silver, Luke W. McLennan, Elspeth A. Beaman, Julian da Silva, Karen Burke Timms, Peter Hogg, Carolyn J. Belov, Katherine |
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using bioinformatics to investigate functional diversity: a case study of mhc diversity in koalas |
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Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas |
| abstract |
Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. Overall, we have provided a bioinformatic workflow for investigating variation in a complex immune gene family from whole genome sequencing data and determined current levels of diversity within koala MHC genes. © The Author(s) 2024 |
| abstractGer |
Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. Overall, we have provided a bioinformatic workflow for investigating variation in a complex immune gene family from whole genome sequencing data and determined current levels of diversity within koala MHC genes. © The Author(s) 2024 |
| abstract_unstemmed |
Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. Overall, we have provided a bioinformatic workflow for investigating variation in a complex immune gene family from whole genome sequencing data and determined current levels of diversity within koala MHC genes. © The Author(s) 2024 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR057959676</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20241023064708.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">241023s2024 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00251-024-01356-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR057959676</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00251-024-01356-6-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.45</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Silver, Luke W.</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-1718-5756</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2024</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2024</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. 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