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8. A collaborative EDNAP exercise on SNaPshot™-based mtDNA control region typing

Author

Weiler, N.E.C., Baca, K., Ballard, D., Balsa, F., Bogus, M., Børsting, C., Brisighelli, F., Červenáková, J., Chaitanya, L., Coble, M., Decroyer, V., Desmyter, S., van der Gaag, K.J., Gettings, K., Haas, C., Heinrich, J., João Porto, M., Kal, A.J., Kayser, M., Kúdelová, A., Morling, N., Mosquera-Miguel, A., Noel, F., Parson, W., Pereira, V., Phillips, C., Schneider, P.M., Syndercombe Court, D., Turanska, M., Vidaki, A., Woliński, P., Zatkalíková, L., and Sijen, T.

Published
2017
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11. Forensic ancestry analysis with two capillary electrophoresis ancestry informative marker (AIM) panels: Results of a collaborative EDNAP exercise

Author

Santos, C., Fondevila, M., Ballard, D., Banemann, R., Bento, A.M., Børsting, C., Branicki, W., Brisighelli, F., Burrington, M., Capal, T., Chaitanya, L., Daniel, R., Decroyer, V., England, R., Gettings, K.B., Gross, T.E., Haas, C., Harteveld, J., Hoff-Olsen, P., Hoffmann, A., Kayser, M., Kohler, P., Linacre, A., Mayr-Eduardoff, M., McGovern, C., Morling, N., O’Donnell, G., Parson, W., Pascali, V.L., Porto, M.J., Roseth, A., Schneider, P.M., Sijen, T., Stenzl, V., Court, D. Syndercombe, Templeton, J.E., Turanska, M., Vallone, P.M., Oorschot, R.A.H.van, Zatkalikova, L., Carracedo, Á., and Phillips, C.

Published
2015
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15. Low-protein diets for broilers: Current knowledge and potential strategies to improve performance and health, and to reduce environmental impact

Author

Woyengo, T. A., Knudsen, K. E.Bach, and Børsting, C. F.

Subjects
Environmental impact, Low protein, Broiler, Performance, Animal Science and Zoology, Gut health
Abstract

Amino acids (AA) are the second most expensive component of broiler diets after energy, and therefore their excessive inclusion in diets can result in significant increase in broiler feed cost. In addition to the increased feed cost, excessive intake of AA by broilers results in increased N excretion, which has negative impact on environment, and welfare of birds and caretakers. Also, excessive intake of AA by broilers results in increased excretion of water and hence increased litter moisture, which has negative impact on environment and welfare of birds. Finally, excessive intake of AA can result in increased production of toxic compounds in hindgut from AA post small intestinal digestion. Thus, methods to reduce dietary CP level without compromising performance of broilers will reduce feed costs and improve the environment, and may improve poultry health and welfare. The dietary level of CP can be reduced without compromising performance of broilers if the resulting low-CP diets are supplemented with crystalline AA to meet the AA requirements of broilers. By supplementing the diets with crystalline AA, the CP values in broiler starter, in this paper any period between hatch and approximately days 21 of age and finisher, in this paper any period between day 21 and day 42 of age, diets can be reduced from approximately 220 and 200 g/kg to 190 and 170 g/kg, respectively, without compromising growth performance of the broilers provided the digestible Lys, Met, Thr, and Val contents in low-CP diets are similar to those in the high-CP diets. The level of CP in broiler starter and finisher diets can be further reduced to 180 g/kg and 160 g/kg, respectively, without compromising growth performance of the broilers if the low-CP diets in addition are supplemented by Gly and the digestible content of Lys, Met, Thr and Val, and Gly are equivalent of the low-CP diets to those in the high-CP diets. Publications delineated in this text indicate several strategies to consider for reducing CP in broiler diets including: feed enzymes, soybean isoflavones, fatty acid type, and fiber type. All these strategies are discussed and gaps in knowledge are identified.

Published
2023

17. List of Contributors

Author

Alfirevic, A., primary, Antonarakis, S.E., additional, Bhardwaj, A., additional, Borry, P., additional, Børsting, C., additional, Busi, M.V., additional, Dissanayake, V.H.W., additional, Festenstein, R., additional, Gaff, C.L., additional, Gomez-Casati, D.F., additional, Grisolía, M., additional, Gupta, P., additional, Haworth, A., additional, Kerr, B., additional, Knoppers, B.M., additional, Korf, B., additional, Kumar, D., additional, Lench, N., additional, Lucassen, A., additional, Macciocca, I., additional, Maher, E., additional, Manolio, T.A., additional, McHale, D., additional, Morling, N., additional, Mutreja, A., additional, Penny, M., additional, Pirmohamed, M., additional, Rajput, N.K., additional, Rogers, Y.-H., additional, Savage, H., additional, Saxena, R., additional, Shabani, M., additional, Sharma, V.K., additional, Singh, V., additional, Sirisena, N., additional, Sumathipala, D., additional, van Langen, I., additional, Wettasinghe, K., additional, Whitworth, J., additional, Wise, A.L., additional, and Zhang, C., additional

Published
2016
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18. Insights into accuracy of social scientists' forecasts of societal change

Author

Grossmann, I., Rotella, A., Hutcherson, C., Sharpinskyi, K., Varnum, M., Achter, S., Dhami, M., Guo, X., Kara-Yakoubian, M., Mandel, D., Raes, L., Tay, L., Vie, A., Wagner, L., Adamkovic, M., Arami, A., Arriaga, P., Bandara, K., Baník, G., Bartoš, F., Baskin, E., Bergmeir, C., Białek, M., Børsting, C., Browne, D., Caruso, E., Chen, R., Chie, B., Chopik, W., Collins, R., Cong, C., Conway, L., Davis, M., Day, M., Dhaliwal, N., Durham, J., Dziekan, M., Elbaek, C., Shuman, E., Fabrykant, M., Firat, M., Fong, G., Frimer, J., Gallegos, J., Goldberg, S., Gollwitzer, A., https://orcid.org/0000-0002-0067-0018, Goyal, J., Graf-Vlachy, L., Gronlund, S., Hafenbrädl, S., Hartanto, A., Hirshberg, M., Hornsey, M., Howe, P., Izadi, A., Jaeger, B., Kačmár, P., Kim, Y., Krenzler, R., Lannin, D., Lin, H., Lou, N., Lua, V., Lukaszewski, A., Ly, A., Madan, C., Maier, M., Majeed, N., March, D., Marsh, A., Misiak, M., Myrseth, K., Napan, J., Nicholas, J., Nikolopoulos, K., O, J., Otterbring, T., Paruzel-Czachura, M., Pauer, S., Protzko, J., Raffaelli, Q., Ropovik, I., Ross, R., Roth, Y., Røysamb, E., Schnabel, L., Schütz, A., Seifert, M., Sevincer, A., Sherman, G., Simonsson, O., Sung, M., Tai, C., Talhelm, T., Teachman, B., Tetlock, P., Thomakos, D., Tse, D., Twardus, O., Tybur, J., Ungar, L., Vandermeulen, D., Williams, L., Vosgerichian, H., Wang, Q., Wang, K., Whiting, M., Wollbrant, C., Yang, T., Yogeeswaran, K., Yoon, S., Alves, V., Andrews-Hanna, J., Bloom, P., Boyles, A., Charis, L., Choi, M., Darling-Hammond, S., Ferguson, Z., Kaiser, C., Karg, S., Ortega, A., Mahoney, L., Marsh, M., Martinie, M., Michaels, E., Millroth, P., Naqvi, J., Ng, W., Rutledge, R., Slattery, P., Smiley, A., Strijbis, O., Sznycer, D., Tsukayama, E., van Loon, A., Voelkel, J., Wienk, M., Wilkening, T., and The Forecasting Collaborative

Abstract

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. Following provision of historical trend data on the domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N=86 teams/359 forecasts), with an opportunity to update forecasts based on new data six months later (Tournament 2; N=120 teams/546 forecasts). Benchmarking forecasting accuracy revealed that social scientists’ forecasts were on average no more accurate than simple statistical models (historical means, random walk, or linear regressions) or the aggregate forecasts of a sample from the general public (N=802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models, and based predictions on prior data.

Published
2022

21. Autosomal SNP typing of forensic samples with the GenPlex™ HID System: Results of a collaborative study

Author

Tomas, C., Axler-DiPerte, G., Budimlija, Z.M., Børsting, C., Coble, M.D., Decker, A.E., Eisenberg, A., Fang, R., Fondevila, M., Frisk Fredslund, S., Gonzalez, S., Hansen, A.J., Hoff-Olsen, P., Haas, C., Kohler, P., Kriegel, A.K., Lindblom, B., Manohar, F., Maroñas, O., Mogensen, H.S., Neureuther, K., Nilsson, H., Scheible, M.K., Schneider, P.M., Sonntag, M.L., Stangegaard, M., Syndercombe-Court, D., Thacker, C.R., Vallone, P.M., Westen, A.A., and Morling, N.

Published
2011
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27. Analysis of Uyghur and Kazakh populations using the Precision ID Ancestry Panel

Author

Simayijiang, H, Børsting, C, Tvedebrink, T, and Morling, N

Subjects
Kazakh, Principal Component Analysis, Massively parallel sequencing, Xinjiang, Ethnic Groups/genetics, High-Throughput Nucleotide Sequencing, GenoGeographer, Sequence Analysis, DNA, DNA Fingerprinting, Polymerase Chain Reaction, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Precision ID Ancestry Panel, Genetics, Population, Gene Frequency, Uyghur, Humans, Ancestry informative markers
Abstract

Autosomal ancestry informative markers (AIMs) are important markers for inferring ancestry of humans. In the present study, we typed 105 Uyghurs and 94 Kazakhs with the Precision ID Ancestry Panel that amplifies 165 autosomal AIMs. No statistically significant deviation from Hardy-Weinberg equilibrium and no linkage disequilibrium between loci was observed after Bonferroni correction. STRUCTURE and PCA analyses showed that Uyghurs and Kazakhs appeared as admixed individuals of primarily European and East Asian ancestry and were clearly differentiated from Europeans, Middle Easterners, South/Central Asians, and East Asians. However, it was not possible to differentiate the two populations from each other and they were also difficult to differentiate from Greenlanders, a population with European/Inuit admixture. GenoGeographer was used to evaluate the weight of the evidence. Initially, the results showed that the majority of AIM profiles from Uyghur and Kazakh individuals were not represented by any of the 36 reference populations of the GenoGeographer database. Consequently, it was not reasonable to infer the ancestry of these individuals. A randomly selected subset of the studied populations (75 Uyghur and 75 Kazakh individuals) was used to construct two new reference populations for GenoGeographer, and ancestry prediction was performed on the remaining test individuals. A total of 42 out of 49 test individuals were represented by at least one population after the introduction of Uyghur and Kazakh reference populations. Likelihood ratios ≥106 were obtained when the alternative hypothesis was that the individual belonged to the South/Central Asian, East Asian, Middle Eastern, European, or the admixed Greenlandic population.

Published
2019

44. Analysis of Uyghur and Kazakh populations using the Precision ID Ancestry Panel

Author

Simayijiang, H., Børsting, C., Tvedebrink, T., Morling, N., Simayijiang, H., Børsting, C., Tvedebrink, T., and Morling, N.

Abstract

Autosomal ancestry informative markers (AIMs) are important markers for inferring ancestry of humans. In the present study, we typed 105 Uyghurs and 94 Kazakhs with the Precision ID Ancestry Panel that amplifies 165 autosomal AIMs. No statistically significant deviation from Hardy-Weinberg equilibrium and no linkage disequilibrium between loci was observed after Bonferroni correction. STRUCTURE and PCA analyses showed that Uyghurs and Kazakhs appeared as admixed individuals of primarily European and East Asian ancestry and were clearly differentiated from Europeans, Middle Easterners, South/Central Asians, and East Asians. However, it was not possible to differentiate the two populations from each other and they were also difficult to differentiate from Greenlanders, a population with European/Inuit admixture. GenoGeographer was used to evaluate the weight of the evidence. Initially, the results showed that the majority of AIM profiles from Uyghur and Kazakh individuals were not represented by any of the 36 reference populations of the GenoGeographer database. Consequently, it was not reasonable to infer the ancestry of these individuals. A randomly selected subset of the studied populations (75 Uyghur and 75 Kazakh individuals) was used to construct two new reference populations for GenoGeographer, and ancestry prediction was performed on the remaining test individuals. A total of 42 out of 49 test individuals were represented by at least one population after the introduction of Uyghur and Kazakh reference populations. Likelihood ratios ≥106 were obtained when the alternative hypothesis was that the individual belonged to the South/Central Asian, East Asian, Middle Eastern, European, or the admixed Greenlandic population.

Published
2019

45. The Danish STR sequence database:duplicate typing of 363 Danes with the ForenSeq™ DNA Signature Prep Kit

Author

Hussing, C., Bytyci, R., Huber, C., Morling, N., Børsting, C., Hussing, C., Bytyci, R., Huber, C., Morling, N., and Børsting, C.

Abstract

Some STR loci have internal sequence variations, which are not revealed by the standard STR typing methods used in forensic genetics (PCR and fragment length analysis by capillary electrophoresis (CE)). Typing of STRs with next-generation sequencing (NGS) uncovers the sequence variation in the repeat region and in the flanking regions. In this study, 363 Danish individuals were typed for 56 STRs (26 autosomal STRs, 24 Y-STRs, and 6 X-STRs) using the ForenSeq™ DNA Signature Prep Kit to establish a Danish STR sequence database. Increased allelic diversity was observed in 34 STRs by the PCR-NGS assay. The largest increases were found in DYS389II and D12S391, where the numbers of sequenced alleles were around four times larger than the numbers of alleles determined by repeat length alone. Thirteen SNPs and one InDel were identified in the flanking regions of 12 STRs. Furthermore, 36 single positions and five longer stretches in the STR flanking regions were found to have dubious genotyping quality. The combined match probability of the 26 autosomal STRs was 10,000 times larger using the PCR-NGS assay than by using PCR-CE. The typical paternity indices for trios and duos were 500 and 100 times larger, respectively, than those obtained with PCR-CE. The assay also amplified 94 SNPs selected for human identification. Eleven of these loci were not in Hardy-Weinberg equilibrium in the Danish population, most likely because the minimum threshold for allele calling (30 reads) in the ForenSeq™ Universal Analysis Software was too low and frequent allele dropouts were not detected.

Published
2019

46. The EUROFORGEN NAME Ampliseq™ custom panel:A second tier panel developed for differentiation of individuals from the Middle East/North Africa

Author

Truelsen, D. M., Pereira, V., Phillips, C., Morling, N., Børsting, C., Truelsen, D. M., Pereira, V., Phillips, C., Morling, N., and Børsting, C.

Abstract

The interest in ancestry informative markers as an investigative tool to identify the biogeographical ancestry of potential suspects is increasing. For this purpose, many different panels have been designed to distinguish individuals from major geographical regions. The EUROFORGEN North Africa and Middle East ancestry panel is a second-tier panel designed for differentiating Middle Eastern/North African populations from other population groups. An Ion AmpliSeq™ custom panel (Thermo Fisher Scientific) was designed to sequence populations of interest using the Ion S5™ (Thermo Fisher Scientific). Of the 111 SNPs selected in the first version of the panel, 107 SNPs were successfully incorporated in the AmpliSeq™ multiplex PCR. More than 600 individuals from 13 different countries in the Middle East, North Africa, and Europe were typed. The performance of the sequencing assay was assessed by calculating relative locus balances, heterozygote balances, and noise levels. Lastly, likelihood ratios were calculated using the GenoGeographer software.

Published
2019

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