13 research outputs found

    ГСнСтичСский Π°Π½Π°Π»ΠΈΠ· останков ΠΈΠ· ΠΏΠΎΠ³Ρ€Π΅Π±Π΅Π½ΠΈΠΉ XVII–XVIII Π²Π². костСла Π‘ΠΎΠΆΡŒΠ΅Π³ΠΎ Π’Π΅Π»Π° Π² НСсвиТС

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    During archaeological excavation in the territory of the Corpus Christi Church in Nesvizh, the regular burials dated to the 17th–18th centuries were discovered. The genetic material extracted from the bones of seven unidentified individuals was analyzed using the forensic genetics approaches, including STR profiling and DNA phenotyping. The genetic examination revealed that the remains of three samples (#1, #2, #6) belonged to women, and the four others (#3, #4, #5, and #7) belonged to men. Autosomal STR-data and Y-chromosomal profiles were obtained for five samples. The kinship analysis excluded that woman #1 and men #3, #4, #5, #7 were first-degree relatives. According to the Y-STR profiles, men #3, #4, #7 referred to the haplogroup R1a, the haplotype of individual #5 corresponded to I2. The both haplogroups are widely represented in Eastern Europe, which, with a high degree of probability, suggests the Slavic origin of the individuals under investigation. To predict eye and hair color, we used the HIrisPlex DNA phenotyping system. The analysis gave the satisfactory results for woman #1 and man #7. In correspondence to the allelic variants of the 24 SNP system, woman #1 had an intermediate type of iris pigmentation and dark blond hair (p = 0.635) with dark shade (0.639), light skin tone, low tendency to sunburn, and a high probability of freckles and pigmented spots of the skin. For male #7, the HIrisPlex model predicted blue eye color with a high probability (p = 0.915), as well as blond hair color (p = 0.915) and light hair color shade (p = 0.962). Our data allow us to conclude that the unknown individuals under investigation have significant genetical and phenotypical similarity with the modern Belarusian population.Π’ Ρ…ΠΎΠ΄Π΅ архСологичСских раскопок Π½Π° Ρ‚Π΅Ρ€Ρ€ΠΈΡ‚ΠΎΡ€ΠΈΠΈ костСла Π‘ΠΎΠΆΡŒΠ΅Π³ΠΎ Π’Π΅Π»Π° Π² НСсвиТС Π±Ρ‹Π»ΠΈ ΠΎΠ±Π½Π°Ρ€ΡƒΠΆΠ΅Π½Ρ‹ рСгулярныС захоронСния XVII–XVIII Π²Π². ΠšΠΎΡΡ‚Π½Ρ‹Π΅ останки сСми нСизвСстных Π»ΠΈΡ† ΠΏΠΎΠ΄Π²Π΅Ρ€Π³Π½ΡƒΡ‚Ρ‹ ΠΈΠ·ΡƒΡ‡Π΅Π½ΠΈΡŽ с использованиСм ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ΠΎΠ² гСнСтичСской экспСртизы ΠΈ Π”ΠΠš-фСнотипирования. Анализ ΠΌΠ°Ρ€ΠΊΠ΅Ρ€ΠΎΠ² ΠΏΠΎΠ»ΠΎΠ²ΠΎΠΉ принадлСТности ΠΏΠΎΠΊΠ°Π·Π°Π», Ρ‡Ρ‚ΠΎ останки ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΠΎΠ² β„– 1, 2 ΠΈ 6 ΠΏΡ€ΠΈΠ½Π°Π΄Π»Π΅ΠΆΠ°Ρ‚ ΠΆΠ΅Π½Ρ‰ΠΈΠ½Π°ΠΌ, ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΠΎΠ² β„– 3, 4, 5 ΠΈ 7 – ΠΌΡƒΠΆΡ‡ΠΈΠ½Π°ΠΌ. Π’ Ρ…ΠΎΠ΄Π΅ исслСдования STR ΠΌΠ°Ρ€ΠΊΠ΅Ρ€ΠΎΠ² аутосомной ΠΈ Y-хромосомной Π”ΠΠš Π±Ρ‹Π»ΠΈ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Ρ‹ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡƒΠ°Π»ΡŒΠ½Ρ‹Π΅ ΠΏΡ€ΠΎΡ„ΠΈΠ»ΠΈ для пяти ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΠΎΠ² ΠΈ ΠΈΡΠΊΠ»ΡŽΡ‡Π΅Π½ΠΎ родство ΠΏΠ΅Ρ€Π²ΠΎΠ³ΠΎ порядка ΠΌΠ΅ΠΆΠ΄Ρƒ ΠΆΠ΅Π½Ρ‰ΠΈΠ½ΠΎΠΉ β„– 1 ΠΈ ΠΌΡƒΠΆΡ‡ΠΈΠ½Π°ΠΌΠΈ β„– 3, 4, 5 ΠΈ 7. Богласно Y-STR профилям ΠΌΡƒΠΆΡ‡ΠΈΠ½Ρ‹ β„– 3, 4, 7 относятся ΠΊ Π³Π°ΠΏΠ»ΠΎΠ³Ρ€ΡƒΠΏΠΏΠ΅ R1a, Π³Π°ΠΏΠ»ΠΎΡ‚ΠΈΠΏ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄Π° β„– 5 соотвСтствуСт Π³Π°ΠΏΠ»ΠΎΠ³Ρ€ΡƒΠΏΠΏΠ΅ I2, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΡˆΠΈΡ€ΠΎΠΊΠΎ прСдставлСны Π½Π° Ρ‚Π΅Ρ€Ρ€ΠΈΡ‚ΠΎΡ€ΠΈΠΈ Восточной Π•Π²Ρ€ΠΎΠΏΡ‹, Ρ‡Ρ‚ΠΎ с высокой Π΄ΠΎΠ»Π΅ΠΉ вСроятности позволяСт ΠΏΡ€Π΅Π΄ΠΏΠΎΠ»Π°Π³Π°Ρ‚ΡŒ славянскоС происхоТдСниС исслСдуСмых Π»ΠΈΡ†. Для установлСния фСнотипичСских особСнностСй ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΠΎΠ² использовали систСму HIrisPlex, Π³Π΅Π½ΠΎΡ‚ΠΈΠΏΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ Π² ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΠΏΠΎΠ»ΡƒΡ‡ΠΈΡ‚ΡŒ ΡƒΠ΄ΠΎΠ²Π»Π΅Ρ‚Π²ΠΎΡ€ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Π΅ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ для ΠΆΠ΅Π½Ρ‰ΠΈΠ½Ρ‹ β„– 1 ΠΈ ΠΌΡƒΠΆΡ‡ΠΈΠ½Ρ‹ β„– 7. Π”Π°Π½Π½Ρ‹Π΅ ΠΎΡ†Π΅Π½ΠΊΠΈ Π°Π»Π»Π΅Π»ΡŒΠ½Ρ‹Ρ… Π²Π°Ρ€ΠΈΠ°Π½Ρ‚ΠΎΠ² 24 SNP систСмы ΡΠ²ΠΈΠ΄Π΅Ρ‚Π΅Π»ΡŒΡΡ‚Π²ΡƒΡŽΡ‚ Π² ΠΏΠΎΠ»ΡŒΠ·Ρƒ славянского Ρ‚ΠΈΠΏΠ° ΠΈΡ… Π²Π½Π΅ΡˆΠ½ΠΎΡΡ‚ΠΈ: с высокой Π²Π΅Ρ€ΠΎΡΡ‚Π½ΠΎΡΡ‚ΡŒΡŽ ΠΆΠ΅Π½Ρ‰ΠΈΠ½Π° β„– 1 ΠΈΠΌΠ΅Π»Π° Π·Π΅Π»Π΅Π½Ρ‹Π΅ Π³Π»Π°Π·Π°, Ρ‚Π΅ΠΌΠ½ΠΎ-русыС волосы ΠΈ свСтлый ΠΎΡ‚Ρ‚Π΅Π½ΠΎΠΊ ΠΊΠΎΠΆΠΈ; ΠΌΡƒΠΆΡ‡ΠΈΠ½Π° β„– 7 являлся свСтлым ΡˆΠ°Ρ‚Π΅Π½ΠΎΠΌ с Π³ΠΎΠ»ΡƒΠ±Ρ‹ΠΌΠΈ Π³Π»Π°Π·Π°ΠΌΠΈ. Π‘ΠΎΠ²ΠΎΠΊΡƒΠΏΠ½ΠΎΡΡ‚ΡŒ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Ρ… Π΄Π°Π½Π½Ρ‹Ρ… позволяСт ΡΠ΄Π΅Π»Π°Ρ‚ΡŒ Π²Ρ‹Π²ΠΎΠ΄, Ρ‡Ρ‚ΠΎ исслСдуСмыС останки ΠΏΡ€ΠΈΠ½Π°Π΄Π»Π΅ΠΆΠ°Ρ‚ прСдставитСлям насСлСния, гСнСтичСски ΠΈ фСнотипичСски схоТСго с соврСмСнной бСлорусской популяциСй

    Вариация ΠΏΠΈΠ³ΠΌΠ΅Π½Ρ‚Π°Ρ†ΠΈΠΈ Ρ€Π°Π΄ΡƒΠΆΠΊΠΈ Π³Π»Π°Π· бСлорусской популяции Π² связи с ΠΏΠΎΠ»ΠΈΠΌΠΎΡ€Ρ„ΠΈΠ·ΠΌΠΎΠΌ Π³Π΅Π½ΠΎΠ² HERC2 ΠΈ OCA2

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    The human genetic phenotyping is one of the most intensely developing area of forensic genetics. Externally visible traits, including eye color, can be predicted by analyzing single nucleotide polymorphisms with a high predictive rate. We studied the polymorphisms rs12913832 and rs1800407 in the HERC2 and OCA2 genes, respectively, to evaluate its prognostic availability in relation to the iris pigmentation of the Belarusian population. For this, both eye images and DNA samples were collected from 314 individuals to analyze the key polymorphisms by the TaqMan assay. Our data confirmed a relevance of rs12913832:A>G and rs1800407:G>A in the prediction context. The highest values of the sensitivity (SE = 0.94) and the specificity (SP = 0.90) were obtained for rs12913832, demonstrating the high efficiency of this marker as a classifier of phenotypic groups. The presence of the ancestral dominant allele rs12913832-A causes a dark (brown) iris pigmentation, how- ever, the heterozygous state rs12913832:GA includes a range of mixed variants. The predictive value of rs1800407 for the genetic phenotyping is highly significant (SE = 0.98), but has a low specificity (SP = 0.14), thus rs1800407, not being an effective classifier, can be used as an auxiliary in the eye color predictive model. The analysis of a cumulative impact of the both poly- morphisms on the iris color variation shows their high prospects for the genetic phenotyping of the Belarusian population.ГСнСтичСскоС Ρ„Π΅Π½ΠΎΡ‚ΠΈΠΏΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ° – Π½ΠΎΠ²ΠΎΠ΅, интСнсивно Ρ€Π°Π·Π²ΠΈΠ²Π°ΡŽΡ‰Π΅Π΅ΡΡ Π½Π°ΠΏΡ€Π°Π²Π»Π΅Π½ΠΈΠ΅ криминалистичСской Π³Π΅Π½Π΅Ρ‚ΠΈΠΊΠΈ. ИсслСдованиС гСнСтичСских основ Ρ†Π²Π΅Ρ‚ΠΎΠ²ΠΎΠΉ Π²Π°Ρ€ΠΈΠ°Ρ†ΠΈΠΈ Π³Π»Π°Π· являСтся ΠΎΠ΄Π½ΠΈΠΌ ΠΈΠ· Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ пСрспСктивных срСди ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ΠΎΠ², Π½Π°Ρ†Π΅Π»Π΅Π½Π½Ρ‹Ρ… Π½Π° установлСниС ΠΎΠ±Π»ΠΈΠΊΠ° нСизвСстного ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄Π° ΠΏΠΎ характСристикам Π΅Π³ΠΎ Π”ΠΠš. Π’ Π΄Π°Π½Π½ΠΎΠΉ Ρ€Π°Π±ΠΎΡ‚Π΅ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΎ ΠΈΠ·ΡƒΡ‡Π΅Π½ΠΈΠ΅ ΠΏΠΎΠ»ΠΈΠΌΠΎΡ€Ρ„ΠΈΠ·ΠΌΠΎΠ² rs12913832 ΠΈ rs1800407 Π² Π³Π΅Π½Π°Ρ… HERC2 ΠΈ ОБA2 соотвСтствСнно Π² связи с ΠΏΠΈΠ³ΠΌΠ΅Π½Ρ‚Π°Ρ†ΠΈΠ΅ΠΉ Ρ€Π°Π΄ΡƒΠΆΠΊΠΈ Π³Π»Π°Π· бСлорусской популяции ΠΈ Π΄Π°Π½Π° ΠΎΡ†Π΅Π½ΠΊΠ° ΠΈΡ… прогностичСской эффСктивности для гСнСтичСского фСнотипирования. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Π΄Π°Π½Π½Ρ‹Π΅ ΠΏΠΎΠ΄Ρ‚Π²Π΅Ρ€Π΄ΠΈΠ»ΠΈ Π·Π½Π°Ρ‡ΠΈΠΌΡ‹ΠΉ Π²ΠΊΠ»Π°Π΄ Π² Ρ†Π²Π΅Ρ‚ΠΎΠ²ΡƒΡŽ Π²Π°Ρ€ΠΈΠ°Ρ†ΠΈΡŽ Ρ€Π°Π΄ΡƒΠΆΠΊΠΈ Π³Π»Π°Π· rs12913832:A>G ΠΈ rs1800407:G>A. ВысокиС значСния Ρ‡ΡƒΠ²ΡΡ‚Π²ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ (SE = 0,94) ΠΈ спСцифичности (SP = 0,90) Π±Ρ‹Π»ΠΈ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Ρ‹ для rs12913832, ΠΏΠΎΠ΄Ρ‚Π²Π΅Ρ€Π΄ΠΈΠ² ΡΡ„Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΌΠ°Ρ€ΠΊΠ΅Ρ€Π° для использования Π² качСствС классификатора фСнотипичСских Π³Ρ€ΡƒΠΏΠΏ. НаличиС ΠΏΡ€Π΅Π΄ΠΊΠΎΠ²ΠΎΠ³ΠΎ Π΄ΠΎΠΌΠΈΠ½Π°Π½Ρ‚Π½ΠΎΠ³ΠΎ аллСля rs12913832-A обусловливаСт Ρ‚Π΅ΠΌΠ½ΡƒΡŽ ΠΏΠΈΠ³ΠΌΠ΅Π½Ρ‚Π°Ρ†ΠΈΡŽ Ρ€Π°Π΄ΡƒΠΆΠΊΠΈ, ΠΎΠ΄Π½Π°ΠΊΠΎ Π³Π΅Ρ‚Π΅Ρ€ΠΎΠ·ΠΈΠ³ΠΎΡ‚Π½ΠΎΠ΅ Π½ΠΎΡΠΈΡ‚Π΅Π»ΡŒΡΡ‚Π²ΠΎ rs12913832:GA Π²ΠΊΠ»ΡŽΡ‡Π°Π΅Ρ‚ Π·Π½Π°Ρ‡ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΉ спСктр ΡΠΌΠ΅ΡˆΠ°Π½Π½Ρ‹Ρ… Π²Π°Ρ€ΠΈΠ°Π½Ρ‚ΠΎΠ². ΠžΠ΄Π½ΠΎΠ½ΡƒΠΊΠ»Π΅ΠΎΡ‚ΠΈΠ΄Π½Ρ‹ΠΉ ΠΏΠΎΠ»ΠΈΠΌΠΎΡ€Ρ„ΠΈΠ·ΠΌ rs1800407 характСризуСтся высокой Ρ‡ΡƒΠ²ΡΡ‚Π²ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΡŒΡŽ (SE = 0,98), ΠΎΠ΄Π½Π°ΠΊΠΎ ΠΈΠΌΠ΅Π΅Ρ‚ Π½ΠΈΠ·ΠΊΠΎΠ΅ Π·Π½Π°Ρ‡Π΅Π½ΠΈΠ΅ спСцифичности (SP = 0,14), ΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ, Π΄Π°Π½Π½Ρ‹ΠΉ ΠΌΠ°Ρ€ΠΊΠ΅Ρ€, Π½Π΅ являясь эффСктивным классификатором, ΠΌΠΎΠΆΠ΅Ρ‚ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒΡΡ Ρ‚ΠΎΠ»ΡŒΠΊΠΎ ΠΊΠ°ΠΊ Π²ΡΠΏΠΎΠΌΠΎΠ³Π°Ρ‚Π΅Π»ΡŒΠ½Ρ‹ΠΉ инструмСнт для прСдсказания Ρ†Π²Π΅Ρ‚Π° Π³Π»Π°Π·. ΠžΡ†Π΅Π½ΠΊΠ° совокупного Π²ΠΊΠ»Π°Π΄Π° ΠΈΠ·ΡƒΡ‡Π΅Π½Π½Ρ‹Ρ… ΠΏΠΎΠ»ΠΈΠΌΠΎΡ€Ρ„ΠΈΠ·ΠΌΠΎΠ² Π² Ρ†Π²Π΅Ρ‚ΠΎΠ²ΡƒΡŽ Π²Π°Ρ€ΠΈΠ°Ρ†ΠΈΡŽ Ρ€Π°Π΄ΡƒΠΆΠΊΠΈ Π³Π»Π°Π· бСлорусской популяции ΠΏΠΎΠΊΠ°Π·Ρ‹Π²Π°Π΅Ρ‚ ΠΈΡ… высокий прогностичСский ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΠ°Π» для гСнСтичСского фСнотипирования

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
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