Unmapped short reads from whole-genome sequencing indicate potential infectious pathogens in German Black Pied cattle
Veterinary Research volume 54, Article number: 95 (2023)
When resequencing animal genomes, some short reads cannot be mapped to the reference genome and are usually discarded. In this study, unmapped reads from 302 German Black Pied cattle were analyzed to identify potential pathogenic DNA. These unmapped reads were assembled and blasted against NCBI’s database to identify bacterial and viral sequences. The results provided evidence for the presence of pathogens. We found sequences of Bovine parvovirus 3 and Mycoplasma species. These findings emphasize the information content of unmapped reads for gaining insight into bacterial and viral infections, which is important for veterinarians and epidemiologists.
Introduction, methods, and results
In livestock genomics, the process of resequencing additional individuals of the same species for which a reference genome exists allows for the investigation of the relationship between sequence variation and diverse phenotypes . Currently, the most widely used technology for resequencing is based on short-read sequencing, where DNA is fragmented into short sequences of 150–300 bp . Raw sequence reads of the resequenced individual are aligned to the reference genome using alignment software such as BWA  or Bowtie2 . Sequence reads that cannot be aligned are called unmapped reads and are usually discarded.
Based on the constructed pangenome of 898 cattle from 57 taurine breeds , up to 83 Mb corresponding to 3.1% of the cattle genome could not be aligned to the current Bos taurus reference genome ARS-UCD1.2, which is derived from a highly inbred Hereford cow . In German Black Pied cattle (DSN, “Deutsches Schwarzbuntes Niederungsrind”), most of the short reads (99.4%) could be mapped to the reference genome, but a small fraction of 0.6% of the reads was left unmapped, on average 2 058 204 reads per animal . The high number of unmapped reads that are discarded during sequencing, especially within large-scale projects such as the 1000 Bull Genomes Project , warrants attention towards the analysis of these reads.
Since unmapped reads passed quality control, sequencing errors can be excluded as a reason why the reads do not align to the reference genome. A more likely reason is that the difference between the reference genome and the resequenced individuals is too big. Thus, longer unmapped regions could point to genomic rearrangements such as structural variants , which are known to occur in cattle genomes but are difficult to detect with short-read sequencing data . Another reason might be that these unmapped reads could belong to DNA of bacterial or viral organisms that were isolated together with the DNA of the investigated animal from the taken sample. These bacterial or viral DNA might arise from potential pathogenic infection of the sequenced individual or from environmental contamination of the sample.
The sample material from which the DNA was isolated might influence the presence of different bacterial or viral organisms. Samples from ear tissue might be contaminated with soil, which is a habitat for many bacteria. Blood samples are most promising for the detection of pathogenic infections, as they are also used in diagnostics. Recently, a study in birds that investigated unmapped reads obtained from RNA sequencing has detected sequences of different pathogens such as Plasmodium and Trypanosoma . In Brown Swiss cattle, preliminary analysis of unmapped DNA short reads provided evidence for the presence of Lactococcus garvieae . This highlights the potential of unmapped reads obtained from whole-genome sequence data to identify pathogens at the population level, which could be of interest to veterinarians and epidemiologists.
We investigated the unmapped reads resulting from whole-genome sequencing using paired-end 150 bp reads of 302 DSN cattle that could not be aligned to the Bos taurus reference genome ARS-UCD1.2. The DSN breed is a small dual-purpose cattle population of 2 500 herdbook cows  that is considered a founder population of the high milk-yielding Holstein cattle . DSN has been reported as a robust breed well adapted to pasture conditions. We hypothesized that pathogenic DNA sequences, besides environmentally ubiquitous microorganisms, could be detected in unmapped reads of those sequenced DSN animals.
Whole-genome sequencing data of 302 DSN animals from eight farms in Germany were available from a previous study . The DNA of those samples was obtained from ear tissue (223 samples), blood (42 samples), or sperm (37 samples), and extracted based on a salt-extraction method . Blood was washed in TE buffer for obtaining a white blood cell pellet. The pellet and the ear tissue were handled in the same way by incubating in 180 µL T1 buffer and 20 µL proteinase K . In the case of sperm, 20 µg DTT was added to the lysis reaction. DNA sequencing was performed on the Illumina NovaSeq 150 PE sequencer resulting in an average 18.72-fold coverage. Processing and filtering of sequencing data followed the 1000 Bull Genomes Project guidelines  using the Bos taurus genome version ARS-UCD1.2_Btau5.0.1Y as reference . This involved trimming low quality bases (qscore < 20) at the beginning and at end of the reads, and filtering out reads with mean qscore < 20 or length < 35 bp using Trimmomatic v.0.9 .
Unmapped reads were retrieved and sorted using samtools v.1.12  (samtools view -u -f 4; samtools sort), including both single and paired-end unmapped reads. Per animal, an average 2 058 204 (SE 180 007) unmapped reads were retrieved out of 348 148 174 (SE 2 669 357) sequence reads that passed quality control. The numbers of unmapped reads per animal ranged from 144 848 to 40 734 422 across the 302 sequenced DSN animals.
Assembly of unmapped reads was performed for each animal using Abyss v.1.5.2 . Kmer sizes from 50 to 90 (maximum kmer size in Abyss) were tested for 30 randomly selected animals (Additional file 1). K-mer refers to a sequence of contiguous nucleotides. That means each unmapped sequence read is used to generate sequences of contiguous nucleotides in a sliding window, where k is the window size in bases. Kmer size = 90 was used for generating contigs since they produced on average the longest contigs and thereby the lowest number of contigs. Based on the information of paired-end reads, gaps between adjacent contigs were linked to create scaffolds (Additional file 2). On average, 11 354 (SE 607) scaffolds with an average length of 779 bp (SE 72 bp) were generated per animal.
Scaffolds with a minimum length of ≥ 500 bp were compared individually to the reference and representative genomes of viruses, prokaryotes, and eukaryotes as obtained from NCBI  (2022/07/18) using Blast + v.2.12.0 software for nucleotides . The NCBI eukaryotes database included the Bos taurus reference genome which is based on a Hereford cow, the Bos indicus assembly which is based on a Nellore bull, and the hybrid Bos indicus x Bos taurus assembly (GCA_003369695.2 UOA_Brahman_1) which is an F1 cross between an Angus sire (Bos taurus) and a Brahman dam (Bos indicus) . From the F1 cross, only the maternal haplotypes of the Bos indicus Brahman breed were available in the database of representative genomes. Each Blast result was sorted according to a matching score, so-called E-value. The smaller the E-value, the stronger the statistical significance. The five top-scoring results from each database of representative genomes were kept (lowest E-value after filtering for query coverage ≥ 95% and identity percentage ≥ 95%). From those top-scoring results of the three databases, only the result with the longest coverage and highest identity percentage was considered.
Scaffolds mapping to the same species were reported as assemblies. When multiple scaffolds mapped to the same species, the corresponding scaffold lengths were summed up to represent the assembly length. Only assemblies covering at least 10% of the investigated genomes of viruses, prokaryotes, and eukaryotes were considered for the further analysis. K-mer depth was calculated as the number of overlapping k-mers per base in the final assemblies. Genes occurring in the assemblies blasted to the Bos species were retrieved using the annotation from NCBI. The presence of pathogenic assemblies was validated using PCR. Primers were designed using NCBI’s Primer-BLAST software .
In the assemblies from unmapped sequence reads of 116 DSN animals, DNA sequences of viruses and bacteria were detected covering at least 10% of the respective viral or bacterial genome. This included the detection of DNA sequences of six viruses and eleven bacterial species. In the unmapped sequence information, the following DNA sequences of viruses were found: 16 DSN animals contained DNA sequences of the Deformed wing virus, four DSN animals contained the Bovine parvovirus 3, four DSN animals contained the Brassica yellows virus, three DSN animals contained the Stenotrophomonas phage SMA7, one DSN animal contained the Helicoverpa armigera densovirus and one DSN animal contained the PreXMRV-1. These are all small viruses with a genome size ranging from 5.33 kb to 10.14 kb (Additional file 3). From this list, the only virus known to frequently infect cattle is the Bovine parvovirus 3. The DNA sequence of Bovine parvovirus 3 was found in animals that were sequenced from either ear tissue or blood samples. The animals were kept in three different farms and ear tissue or blood were collected in different years (Table 1).
With regard to bacterial species, the unmapped sequence information of 37 DSN animals contained DNA sequences of Achromobacter insuavis, while Variovorax gossypii was found in 18 DSN animals, Roseateles aquatilis in 12 DSN animals, Bosea lupini in nine DSN animals, Mycoplasma wenyonii str. Massachusetts in four DSN animals, Pseudomonas paracarnis in three DSN animals, Candidatus Mycoplasma haemobos in two DSN animals, and Delftia acidovorans, Pseudomonas carnis, Pseudomonas lactis, and Pseudomonas salmasensis each in one DSN animal (Additional file 4). Of those, only the Mycoplasma species naturally infect cattle, while the Pseudomonas species are known to proliferate in stored beef and milk. The other bacteria are found primarily in soil. Interestingly, Mycoplasma species were only detected in blood samples, and Pseudomonas only in sperm samples (Table 2). For one cow, DNA sequences of both Candidatus Mycoplasma haemobos and Mycoplasma wenyonii were detected, covering their genome with 11.29% and 33.71%, respectively.
The presence of Candidatus Mycoplasma haemobos and Mycoplasma wenyonii was validated using PCR (Additional file 5). Among four animals detected with Mycoplasma wenyonii in the unmapped reads, three had enough DNA for a validation PCR. In the DNA of all three animals PCR fragments of Mycoplasma wenyonii could be amplified using primers targeting the 23S rRNA region. The two animals detected with Candidatus Mycoplasma haemobos also showed strong amplification for Candidatus Mycoplasma haemobos in the PCR, but a weak amplification was also observed in two out of three negative controls. The PCR primers were also flanking the 23S rRNA. No amplification was obtained for Bovine parvovirus 3 although two different sets of primers were tested (Additional file 5).
The unmapped reads of the investigated DSN animals showed no evidence for the presence of foreign eukaryotic DNA, with assemblies covering > 10% of the foreign eukaryotic genomes. However, smaller assemblies obtained from all 302 DSN animals could be mapped to different Bos species including Bos indicus, Bos indicus x Bos taurus, and Bos mutus. The average assembly length of these smaller assemblies was 341.3 kb (SE 6.9 kb) corresponding to 0.01% of the cattle reference genome. These assemblies spanned genomic regions of 388 genes, which were covered by assemblies from unmapped sequence information of on average 19.9% of the 302 DSN animals. Around 80% of the DSN animals had sequences covering ten genes. These ten genes are located on eight chromosomes: THSD7B (Thrombospondin type 1 domain containing 7B) on chromosome 2, VTCN1 (V-set domain containing T cell activation inhibitor 1) on chromosome 3, SAMD9 (Sterile alpha motif domain containing 9) on chromosome 4, LOC109559963 (rho GTPase-activating protein 20-like) on chromosome 6, RASGRF2 (Ras protein specific guanine nucleotide releasing factor 2) on chromosome 7, NDUFAF2 (NADH:ubiquinone oxidoreductase complex assembly factor 2) on chromosome 20, LOC113881290 (heat shock 70 kDa protein 1A) and PKHD1 (PKHD1 ciliary IPT domain containing fibrocystin/polyductin) on chromosome 23, and TCERG1L (transcription elongation regulator 1 like) and SUFU (SUFU negative regulator of hedgehog signaling) on chromosome 26.
In this study, we identified pathogenic DNA sequences of Mycoplasma species and Bovine parvovirus 3 based solely on usually discarded unmapped reads from whole-genome sequencing data. These could point to bovine pathogens, but also to potential biological contaminations. The in silico detected Mycoplasma on the unmapped reads could be validated using PCR, while PCR validation could not be provided for Bovine parvovirus 3. Furthermore, we provide evidence that the detection of pathogens depends on the tissue from which the DNA was extracted. For example, Mycoplasma was detected only when blood and not sperm or ear tags were used for DNA extraction.
The reliability for detecting the correct bacterial and virus species in the sequence information of DSN was built upon assemblies that mapped to more than 10% of the representative pathogen genome, and on parameters such as contiguity (number of scaffolds) and k-mer depth (coverage of k-mer in assemblies). Although less reliable, shorter assemblies covering less than 10% of the pathogen genome indicated the potential presence of Mycoplasma in more DSN animals and the presence of Bovine gammaherpesvirus 6 (data not shown).
Infection with the Bovine parvovirus 3, which was found in the unmapped sequence information of four DSN animals, has been linked so far only to bovine respiratory disease [23, 24]. However, cases of diarrhea in neonatal calves and respiratory and reproductive diseases in adult cattle have been associated with other bovine parvoviruses . More recently, viral metagenomics analyses revealed that Bovine parvovirus 3 is the most abundant virus in fetal bovine serum on almost all continents . The other viruses detected in the unmapped sequence information of DSN are environmental viruses which do not infect cattle.
The detection of Mycoplasma in DSN was expected, since the presence of this pathogen is known and linked to mastitis infections [27, 28]. DSN cows with mastitis are routinely tested for Mycoplasma together with other bacterial infections. However, the classification of Mycoplasma at species level is novel. Recently, Candidatus Mycoplasma haemobos has been identified in cattle in Northern Germany for the first time . This is the region where most of the DSN animals come from. In the same study, infections with Mycoplasma wenyonii were reported . Coinfection with both Mycoplasma species have been reported in different places [30, 31]. Interestingly, using DNA sequence analysis of unmapped reads, we could also identify one animal that was detected with DNA of both Mycoplasma species. Furthermore, infections with Candidatus Mycoplasma haemobos and Mycoplasma wenyonii had been detected in blood only [29,30,31,32,33].
Some pathogens were detected only in DNA extracted from specific tissues. DNA sequences of Mycoplasma, for example, were detected only in DNA extracted from blood, while soil bacteria such as Variovorax gossypii  and Bosea lupini  were detected mainly in DNA extracted from ear tissue clips, pointing to potential sample contamination. Pseudomonas has been reported before in bovine raw milk and refrigerated beef [36, 37]. In our study, we detected this species only in unmapped sequence information obtained from sperm samples.
This study presents an analysis of unmapped reads obtained from cattle previously sequenced. For further validation of microorganisms that are not typically infectious in cattle, it would also be necessary to validate their occurrence via PCR or direct detection which would serve as evidence of biological contamination. Since contamination via ubiquitous microorganisms varies among different tissue types, we emphasize the importance of collecting tissue-specific metadata, ensuring this valuable information is available for drawing conclusions.
Furthermore, the lack of Bos taurus results from the Blast analysis was anticipated, as the assemblies were generated from sequence reads that did not initially map to the Bos taurus reference genome. The fact that some assemblies from the unmapped reads of DSN could be mapped to other Bos species suggests that the current Bos taurus reference genome cannot capture all of the sequence variation found in DSN. Repetitive regions such as simple repeats, tandem repetitions, microsatellites, and even short and long interspersed nuclear elements, and structural variations such as insertions, and tandem duplications are huge challenges in sequence alignment . For the identified genes that were covered by 80% of the DSN assemblies, observations about structural variants in the Ensembl database release 109 were found. For instance, two deletions (esv4015120 and esv4018365) and one tandem duplication (esv3899898) are known for VTCN1, seven deletions (esv3896092, esv4013846, esv4018847, esv4013542, esv4019566, esv4014539, and esv3896170) and one insertion (nsv810851) for RASGRF2, and two deletions (esv3894860 and esv4012358), two inversions (esv3897812 and esv3897810), and one tandem duplication (esv3899664) for PKHD1. Therefore, DNA sequences that map to other Bos species than the Herford reference genome for Bos taurus point to potential structural variations occurring in DSN which should be better characterized in the future with other mapping strategies, such as applied in the pangenome consortium  and the utilization of long-read sequencing data by the long-read consortium for cattle .
In conclusion, we revealed for the first time the presence of Candidatus Mycoplasma haemobos and Mycoplasma wenyonii in DSN by using information from unmapped reads of short-read sequencing data. The unmapped short reads could also provide evidence for infections if other data is lacking. Further investigations of unmapped short reads are needed in order to elucidate the reliable use of such information which can be very useful for veterinarians and epidemiologists, in particular to understudied animal health in populations.
Availability of data and materials
Publicly available datasets were analyzed in this study. This data can be found here: https://www.ebi.ac.uk/ena/browser/view/PRJEB45822.
Stratton M (2008) Genome resequencing and genetic variation. Nat Biotechnol 26:65–66. https://doi.org/10.1038/nbt0108-65
Shendure J, Ji H (2008) Next-generation DNA sequencing. Nat Biotechnol 26:1135–1145. https://doi.org/10.1038/nbt1486
Li H, Durbin R (2010) Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26:589–595. https://doi.org/10.1093/bioinformatics/btp698
Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357–360. https://doi.org/10.1038/nmeth.1923
Zhou Y, Yang L, Han X, Han J, Hu Y, Li F, Xia H, Peng L, Boschiero C, Rosen BD, Bickhart DM, Zhang S, Guo A, Tassell CP, Van, Smith TPL, Yang L, Liu GE (2022) Assembly of a pangenome for global cattle reveals missing sequences and novel structural variations, providing new insights into their diversity and evolutionary history. Genome Res 32:1585–1601. https://doi.org/10.1101/GR.276550.122
Rosen BD, Bickhart DM, Schnabel RD, Koren S, Elsik CG, Tseng E, Rowan TN, Low WY, Zimin A, Couldrey C, Hall R, Li W, Rhie A, Ghurye J, McKay SD, Thibaud-Nissen F, Hoffman J, Murdoch BM, Snelling WM, McDaneld TG, Hammond JA, Schwartz JC, Nandolo W, Hagen DE, Dreischer C, Schultheiss SJ, Schroeder SG, Phillippy AM, Cole JB, Van Tassell CP, Liu G, Smith TPL, Medrano JF (2020) De novo assembly of the cattle reference genome with single-molecule sequencing. Gigascience 9:giaa021. https://doi.org/10.1093/gigascience/giaa021
Neumann GB, Korkuć P, Arends D, Wolf MJ, May K, Reißmann M, Elzaki S, König S, Brockmann GA (2021) Design and performance of a bovine 200 k SNP chip developed for endangered german black Pied cattle (DSN). BMC Genomics 22:905. https://doi.org/10.1186/S12864-021-08237-2
Hayes BJ, Daetwyler HD (2019) 1000 bull genomes project to map simple and complex genetic traits in cattle: applications and outcomes. Annu Rev Anim Biosci 7:89–102. https://doi.org/10.1146/annurev-animal-020518
Hasan MS, Wu X, Zhang L (2019) Uncovering missed indels by leveraging unmapped reads. Sci Rep 9:1–14. https://doi.org/10.1038/s41598-019-47405-z
Talenti A, Powell J, Hemmink JD, Cook EAJ, Wragg D, Jayaraman S, Paxton E, Ezeasor C, Obishakin ET, Agusi ER, Tijjani A, Amanyire W, Muhanguzi D, Marshall K, Fisch A, Ferreira BR, Qasim A, Chaudhry U, Wiener P, Toye P, Morrison LJ, Connelley T, Prendergast JGD (2022) A cattle graph genome incorporating global breed diversity. Nat Commun 13:910. https://doi.org/10.1038/s41467-022-28605-0
Laine VN, Gossmann TI, Van Oers K, Visser ME, Groenen MAM (2019) Exploring the unmapped DNA and RNA reads in a songbird genome. BMC Genomics 20:19. https://doi.org/10.1186/S12864-018-5378-2
Szyda J, Mielczarek M (2018) Understanding unmapped reads using Bos taurus whole genome DNA sequence. In: 69th Annual Meeting of the European Federation of Animal Science. EAAP, Dubrovnik
TGRDEU (2021) Rind: Deutsches Schwarzbuntes Niederungsrind. https://tgrdeu.genres.de/nutztiere/suche-nutztiere/genetik-detaildarstellung/?tx_sttgrdeu_nutztier%5Baction%5D=genetikDetail&tx_sttgrdeu_nutztier%5Bcontroller%5D=Nutztier&tx_sttgrdeu_nutztier%5Bg_id%5D=654&cHash=961248c5168bd52ab4538b0d7506f9e8. Accessed 28 Feb 2022
Neumann GB, Korkuć P, Arends D, Wolf MJ, May K, König S, Brockmann GA (2023) Genomic diversity and relationship analyses of endangered german black Pied cattle (DSN) to 68 other taurine breeds based on whole-genome sequencing. Front Genet 13:993959. https://doi.org/10.3389/FGENE.2022.993959
Reissmann M, Lutz W, Lieckfeldt D, Sandoval-Castellanos E, Ludwig A (2020) An agouti-signaling-protein mutation is strongly associated with melanism in european roe deer (Capreolus capreolus). Genes (Basel) 11:647. https://doi.org/10.3390/GENES11060647
Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120. https://doi.org/10.1093/bioinformatics/btu170
Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST, McVean G, Durbin R (2011) The variant call format and VCFtools. Bioinformatics 27:2156–2158. https://doi.org/10.1093/bioinformatics/btr330
Jackman SD, Vandervalk BP, Mohamadi H, Chu J, Yeo S, Hammond SA, Jahesh G, Khan H, Coombe L, Warren RL, Birol I (2017) ABySS 2.0: resource-efficient assembly of large genomes using a bloom filter. Genome Res 27:768–777. https://doi.org/10.1101/gr.214346.116
Sayers EW, Bolton EE, Brister JR, Canese K, Chan J, Comeau DC, Connor R, Funk K, Kelly C, Kim S, Madej T, Marchler-Bauer A, Lanczycki C, Lathrop S, Lu Z, Thibaud-Nissen F, Murphy T, Phan L, Skripchenko Y, Tse T, Wang J, Williams R, Trawick BW, Pruitt KD, Sherry ST (2022) Database resources of the National center for biotechnology information. Nucleic Acids Res 50:20–26. https://doi.org/10.1093/NAR/GKAB1112
Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL (2009) BLAST+: Architecture and applications. BMC Bioinformatics 10:421. https://doi.org/10.1186/1471-2105-10-421
Koren S, Rhie A, Walenz BP, Dilthey AT, Bickhart DM, Kingan SB, Hiendleder S, Williams JL, Smith TPL, Phillippy AM (2018) De novo assembly of haplotype-resolved genomes with trio binning. Nat Biotechnol 36:1174–1182. https://doi.org/10.1038/nbt.4277
Ye J, Coulouris G, Zaretskaya I, Cutcutache I, Rozen S, Madden TL (2012) Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction. BMC Bioinform 13:134. https://doi.org/10.1186/1471-2105-13-134
Jager MC, Tomlinson JE, Lopez-Astacio RA, Parrish CR, Van de Walle GR (2021) Small but mighty: old and new parvoviruses of veterinary significance. Virol J 18:210. https://doi.org/10.1186/S12985-021-01677-Y
Nagy A, Abdallah F, El Damaty HM, Tariq A, Merwad AMA, Alhatlani BY, Elsohaby I (2022) Genetic characterization of upper respiratory tract virome from nonvaccinated egyptian cow-calf operations. PLoS One 17:e0267036. https://doi.org/10.1371/JOURNAL.PONE.0267036
MacLachlan NJ, Dubovi EJ (2011) Parvoviridae Fenner’s veterinary virology. Academic press, Cambridge
Zhang P, Cao L, Ma YY, Su B, Zhang CY, Li YP (2022) Metagenomic analysis reveals presence of different animal viruses in commercial fetal bovine serum and trypsin. Zool Res 43:756–766. https://doi.org/10.24272/J.ISSN.2095-8137.2022.093
Maunsell FP, Woolums AR, Francoz D, Rosenbusch RF, Step DL, Wilson DJ, Janzen ED (2011) Mycoplasma bovis infections in cattle. J Vet Intern Med 25:772–783. https://doi.org/10.1111/J.1939-1676.2011.0750.X
Gelgie AE, Korsa MG, Kerro Dego O (2022) Mycoplasma bovis mastitis. Curr Res Microb Sci 3:100123. https://doi.org/10.1016/j.crmicr.2022.100123
Hoelzle K, Winkler M, Kramer MM, Wittenbrink MM, Dieckmann SM, Hoelzle LE (2011) Detection of Candidatus Mycoplasma haemobos in cattle with anaemia. Vet J 187:408–410. https://doi.org/10.1016/J.TVJL.2010.01.016
Schambow RA, Poulsen K, Bolin S, Krahn D, Norby B, Sockett D, Ruegg PL (2021) Apparent prevalence of Mycoplasma wenyonii, Candidatus Mycoplasma haemobos, and bovine leukemia virus in Wisconsin and Michigan dairy cattle herds. JDS Commun 2:61–66. https://doi.org/10.3168/JDSC.2020-0033
Niethammer FM, Ade J, Hoelzle LE, Schade B (2018) Hemotrophic mycoplasma in Simmental cattle in Bavaria: prevalence, blood parameters, and transplacental transmission of Candidatus Mycoplasma haemobos and Mycoplasma wenyonii. Acta Vet Scand 60:74. https://doi.org/10.1186/S13028-018-0428-Y
Gladden N, Haining H, Henderson L, Marchesi F, Graham L, McDonald M, Murdoch FR, Bruguera Sala A, Orr J, Ellis K (2016) A case report of Mycoplasma wenyonii associated immune-mediated haemolytic anaemia in a dairy cow. Ir Vet J 69:1. https://doi.org/10.1186/S13620-016-0061-X
Tagawa M, Matsumoto K, Inokuma H (2008) Molecular detection of Mycoplasma wenyonii and ‘Candidatus Mycoplasma haemobos’ in cattle in Hokkaido. Japan Vet Microbiol 132:177–180. https://doi.org/10.1016/J.VETMIC.2008.05.006
Kämpfer P, Busse HJ, McInroy JA, Glaeser SP (2015) Variovorax gossypii sp. nov., isolated from Gossypium hirsutum. Int J Syst Evol Microbiol 65:4335–4340. https://doi.org/10.1099/IJSEM.0.000581
De Meyer SE, Willems A (2012) Multilocus sequence analysis of Bosea species and description of Bosea lupini sp. nov., Bosea lathyri sp. nov. and Bosea robiniae sp. nov., isolated from legumes. Int J Syst Evol Microbiol 62:2505–2510. https://doi.org/10.1099/IJS.0.035477-0
Lick S, Wibberg D, Winkler A, Blom J, Grimmler C, Goesmann A, Kalinowski J, Kröckel L (2021) Pseudomonas paracarnis sp. nov., isolated from refrigerated beef. Int J Syst Evol Microbiol 71:004652. https://doi.org/10.1099/IJSEM.0.004652
Von Neubeck M, Huptas C, Glück C, Krewinkel M, Stoeckel M, Stressler T, Fischer L, Hinrichs J, Scherer S, Wenning M (2017) Pseudomonas lactis sp. nov. and Pseudomonas paralactis sp. nov., isolated from bovine raw milk. Int J Syst Evol Microbiol 67:1656–1664. https://doi.org/10.1099/IJSEM.0.001836
Tørresen OK, Star B, Mier P, Andrade-Navarro MA, Bateman A, Jarnot P, Gruca A, Grynberg M, Kajava AV, Promponas VJ, Anisimova M, Jakobsen KS, Linke D (2019) Tandem repeats lead to sequence assembly errors and impose multi-level challenges for genome and protein databases. Nucleic Acids Res 47:10994–11006. https://doi.org/10.1093/NAR/GKZ841
Smith TPL, Bickhart DM, Boichard D, Chamberlain AJ, Djikeng A, Jiang Y, Low WY, Pausch H, Demyda-Peyrás S, Prendergast J, Schnabel RD, Rosen BD (2023) The bovine Pangenome Consortium: democratizing production and accessibility of genome assemblies for global cattle breeds and other bovine species. Genome Biol 24:139. https://doi.org/10.1186/S13059-023-02975-0
Nguyen TV, Vander Jagt CJ, Wang J, Daetwyler HD, Xiang R, Goddard ME, Nguyen LT, Ross EM, Hayes BJ, Chamberlain AJ, MacLeod IM (2023) In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants. Genet Sel Evol 55:9. https://doi.org/10.1186/S12711-023-00783-5
We acknowledge the Rinderproduktion Berlin-Brandenburg GmbH and DSN farms for supporting this project with data, tissue collection, and their expertise in animal selection. Additionally, we acknowledge the support of Dorothea Schemmel in the laboratory for sample preparation and PCR. Finally, we thank Erik Leipe for language editing.
Open Access funding enabled and organized by Projekt DEAL. This work was financially supported by the German Federal Ministry of Food and Agriculture (BMEL) based on a decision of the Parliament of the Federal Republic of Germany, granted by the Federal Office for Agriculture and Food (BLE), grant number FKZ2818BM090 and 091.
Ethics approval and consent to participate
Ethical review and approval were not required for the animal study because samples were previously collected based on routine procedures on these farm animals. Ear tags were taken as part of the required registration procedure, blood samples were taken by a trained veterinarian to perform standard health recording. Written informed consent was obtained from the animal owners for the participation of their animals in this study.
The authors declare that they have no competing interests.
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Additional file 1: Average number of contigs and N50 of assembled unmapped reads from 30 randomly selected DSN animals.
K-mer sizes from 50 to 90 were tested.
(1) Unmapped sequence reads (~150bp) were first extracted from alignment files. (2) K-mers were generated from unmapped reads with sliding window size of 90 bp and step size of 1 bp, producing around 61 k-mers per unmapped read. (3) Based on the k-mers similarities and on the de-Bruijn graph algorithm implemeted by Abyss, contigs were formed. (4) Contigs were linked together whenever possible based on the paired-end reads used to generate the k-mers. (5) The resulting assemblies for each species consist of scaffolds that were sorted according to their blast results
Additional file 3: Average assembly and animal sample count information for detected viruses in 27 DSN cattle.
Those were Deformed wing virus (DWV), Bovine parvovirus 3 (BP3), Brassica yellows virus (BYV), Stenotrophomonas phage SMA7 (SMA7), and Helicoverpa armigera densovirus (HAD). Arithmetic means are given for assembly size, k-mer depth, number of scaffolds, and genome cover, with standard errors given in parenthesis.
Additional file 4: Average assembly and animal sample count information for detected bacteria in DSN cattle.
Arithmetic means are given for assembly size, k-mer depth, number of scaffolds, and genome cover, with standard errors given in parenthesis.
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Neumann, G.B., Korkuć, P., Reißmann, M. et al. Unmapped short reads from whole-genome sequencing indicate potential infectious pathogens in German Black Pied cattle. Vet Res 54, 95 (2023). https://doi.org/10.1186/s13567-023-01227-0