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African wild dogs (Lycaon pictus) have undergone severe population reductions and are listed as endangered on the International Union for Conservation of Nature Red List. Small, isolated populations have the potential to suffer from threats to their genetic diversity that may impact species viability and future survival. This study provides the first set of population-wide genomic data to address conservation concerns for this endangered species. Whole genome sequencing data were generated for 71 free-ranging African wild dogs from the Kruger National Park (KNP), South Africa, and used to estimate important population genomic parameters. Genomic diversity metrics revealed that variation levels were low; however, this African wild dog population showed low levels of inbreeding. Very few first- and second-order relationships were observed in this cohort, with most relationships falling into the third-order or distant category. Patterns of homozygosity could have resulted from historical inbreeding or a loss in genome variation due to a population bottleneck. Although the results suggest that this stronghold African wild dog population maintains low levels of inbreeding, likely due to their cooperative breeding system, it may lead to a continuous population decline when a reduced number of suitable mates are available. Consequently, the low genomic variation may influence species viability over time. This study highlights the importance of assessing population genomic parameters to set conservation priorities. Future studies should include the investigation of the potential of this endangered species to adapt to environmental changes considering the low genomic diversity in this population.
African wild dogs (Lycaon pictus) have undergone severe population reductions and are listed as endangered on the International Union for Conservation of Nature Red List. Small, isolated populations have the potential to suffer from threats to their genetic diversity that may impact species viability and future survival. This study provides the first set of population-wide genomic data to address conservation concerns for this endangered species. Whole genome sequencing data were generated for 71 free-ranging African wild dogs from the Kruger National Park (KNP), South Africa, and used to estimate important population genomic parameters. Genomic diversity metrics revealed that variation levels were low; however, this African wild dog population showed low levels of inbreeding. Very few first- and second-order relationships were observed in this cohort, with most relationships falling into the third-order or distant category. Patterns of homozygosity could have resulted from historical inbreeding or a loss in genome variation due to a population bottleneck. Although the results suggest that this stronghold African wild dog population maintains low levels of inbreeding, likely due to their cooperative breeding system, it may lead to a continuous population decline when a reduced number of suitable mates are available. Consequently, the low genomic variation may influence species viability over time. This study highlights the importance of assessing population genomic parameters to set conservation priorities. Future studies should include the investigation of the potential of this endangered species to adapt to environmental changes considering the low genomic diversity in this population.
15Background. BGISEQ-500 is based on DNBSEQ TM technology and superior in 16 providing high outputs and requiring less cost. This sequencer has been widely used in 17 various areas of scientific and clinical research. A better understanding of the sequencing 18 process and sequencer performance is essential for stabilizing sequencing process, 19 accurately interpreting sequencing results and efficiently solving sequencing troubles. To 20 solve these problems, a comprehensive database SEQdata-BEACON was constructed to 21 accumulate sequencing performance data in BGISEQ-500. 22 Methods. Totally 60 BGISEQ-500 sequencers in BGI-Wuhan lab were used to collect the 23 sequencing performance data. Those lanes in paired-end 100 sequencing using 10bp 24 2 barcode were chosen, and each lane containing 66 metrics was assigned a unique entry 25 number as ID. The database was constructed in MySQL server 8.0 and the website was 26 built on Apache (2.4.33 win64 VC15 server). The statistical analysis and linear regression 27 models were generated by R program based on the data from Results. A total of 2236 entries were recorded in the database, including sample ID, 30 yield, quality, machine state and supplies information. According to correlation matrix, 31 the 52 numerical metrics were clustered into three groups signifying yield-quality, 32 machine state and sequencing calibration. The metrics distributions also delivered some 33 patterns and rendered clues for further explanation or analysis of the sequencing process. 34 Using the data of total 200 cycles, the linear regression model well simulated the final 35 outputs. Moreover, the predicted final yield could be provided in the 15 th cycle of the 36 early stage of sequencing and the corresponding coefficient of determination R 2 of the 37 200 th and 15 th cycle models were 0.97 and 0.81 respectively. The data source, statistical 38 findings and application tools were all available in our website 39 http://seqBEACON.genomics.cn:443/home.html. These resources can be used as a 40 constantly updated reference for BGISEQ-500 users to comprehensively understand 41 DNBSEQ TM technology, solve sequencing problems and optimize the sequencing 42 process.43
BackgroundThe sequencing platform BGISEQ-500 is based on DNBSEQ technology and provides high throughput with low costs. This sequencer has been widely used in various areas of scientific and clinical research. A better understanding of the sequencing process and performance of this system is essential for stabilizing the sequencing process, accurately interpreting sequencing results and efficiently solving sequencing problems. To address these concerns, a comprehensive database, SEQdata-BEACON, was constructed to accumulate the run performance data in BGISEQ-500.ResultsA total of 60 BGISEQ-500 instruments in the BGI-Wuhan lab were used to collect sequencing performance data. Lanes in paired-end 100 (PE100) sequencing using 10 bp barcode were chosen, and each lane was assigned a unique entry number as its identification number (ID). From November 2018 to April 2019, 2236 entries were recorded in the database containing 65 metrics about sample, yield, quality, machine state and supplies information. Using a correlation matrix, 52 numerical metrics were clustered into three groups signifying yield-quality, machine state and sequencing calibration. The distributions of the metrics also delivered information about patterns and rendered clues for further explanation or analysis of the sequencing process. Using the data of a total of 200 cycles, a linear regression model well simulated the final outputs. Moreover, the predicted final yield could be provided in the 15th cycle of the early stage of sequencing, and the corresponding R2 of the 200th and 15th cycle models were 0.97 and 0.81, respectively. The model was run with the test sets obtained from May 2019 to predict the yield, which resulted in an R2 of 0.96. These results indicate that our simulation model was reliable and effective.ConclusionsData sources, statistical findings and application tools provide a constantly updated reference for BGISEQ-500 users to comprehensively understand DNBSEQ technology, solve sequencing problems and optimize run performance. These resources are available on our website http://seqBEACON.genomics.cn:443/home.html.
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