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Introdução: Métodos quantitativos sensíveis e acurados para monitorar o quimerismo hematopoiético após Transplante de Células-Tronco Hematopoiéticas (TCTH) são necessários para verificar o sucesso do enxerto, uma vez que os resultados influenciam a abordagem terapêutica. Método: A técnica de detecção de DNA baseada em primers inserção-específicos de marcadores genéticos do tipo InDel (Inserção/Deleção) foi avaliada quanto a sua utilidade em quantificar quimerismo em amostras de DNA em baixa concentração, em PCR em Tempo Real (qPCR). Para isso, amostras de DNA de dez pacientes submetidos a Transplante de Medula Óssea (TMO) foram analisados para quantificar a concentração de DNA residual em diferentes períodos pós-transplante. Os resultados obtidos pela InDelqPCR foram comparados com a evolução clínica descrita nos prontuários. Resultados: As quantificações do DNA residual variaram de 0,021 ng/µL a 11,71 ng/µL, correspondendo a fração de 0,065% a 40,6% do DNA total presente na amostra. Os resultados obtidos (presença ou ausência do alelo inserção) foram condizentes com a evolução clínica dos pacientes, em alguns casos, evidenciando quimerismo prévio ao relatado nos prontuários. Conclusão: Nossos dados demonstram a utilidade do método InDel-qPCR, baseada em primers inserçãoespecíficos, no monitoramento de quimerismo hematopoiético. / Introduction: Sensitive and accurate quantitative methods to monitor hematopoietic chimerism after Hematopoietic Stem Cell Transplantation (HSCT) are necessary to evaluate engraftment since the results influence a therapeutic approach. Method: DNA detection technique based on insert-specific primers for Insertion/Deletion polymorphism (InDel) was evaluated for chimerism quantification of samples with low amounts of DNA, by quantitative real-time polymerase chain reaction (qPCR). Samples of patients undergoing Bone Marrow Transplantation (BMT) collected at different post-transplantation times were analyzed to quantify the residual DNA concentration. Then, the results found using InDel-qPCR were compared to the medical records. Results: DNA quantifications ranged from 0.021 ng/?L to 11.71 ng/?L, corresponding to a fraction of 0.065% to 40.6% of the total DNA. Our results, in some cases, shows chimerism presence previously to that reported in the medical records. Conclusion: Our data demonstrate the usefulness of the InDelqPCR method based on insertion-specific primers in the monitoring of hematopoietic chimerism.

With the development of sequencing technologies, more and more sequence variants are available for investigation. Different types of variants in the human genome have been identified, including single nucleotide polymorphisms (SNPs), short insertions and deletions (indels), and large structural variations such as large duplications and deletions. Of great research interest is the functional effects of these variants. Although many programs have been developed to predict the effect of SNPs, few can be used to predict the effect of indels or multiple variants, such as multiple SNPs, multiple indels, or a combination of both. Moreover, fine grained prediction of the functional outcome of variants is not available. To address these limitations, we developed a prediction framework, HMMvar, to predict the functional effects of coding variants (SNPs or indels), using profile hidden Markov models (HMMs). Based on HMMvar, we proposed HMMvar-multi to explore the joint effects of multiple variants in the same gene. For fine grained functional outcome prediction, we developed HMMvar-func to computationally define and predict four types of functional outcome of a variant: gain, loss, switch, and conservation of function. / Ph. D.

Dezoito galinhas de uma população experimental utilizada em um cruzamento recíproco entre as linhagens de frangos de corte (TT) e de postura (CC) foram sequenciadas pela tecnologia de nova geração na plataforma Illumina com uma cobertura média de 10X. A descoberta de variantes genéticas foi realizada em uma região de locos de característica quantitativa (Quantitative Trait Locus, QTL), associado anteriormente com peso e percentagem de gordura abdominal no cromossomo 3 da galinha (GGA3), entre os marcadores microssatélites LEI0161 e ADL0371 (33,595,706-42,632,651 pb). O programa SAMtools foi utilizado na identificação de 136.054 SNPs únicos e 15.496 INDELs únicas nos 18 animais sequenciados e após a filtragem das mutações, 92.518 SNPs únicos e 9.298 INDELs únicas foram mantidas. Uma lista de 77 genes foi analisada buscando genes relacionados ao metabolismo de lipídios. Variantes localizadas na região codificante (386 SNPs e 15 INDELs) foram identificadas e associadas com vias metabólicas importantes. Variantes nos genes LOC771163, EGLN1, GNPAT, FAM120B, THBS2 e GGPS1 foram identificadas e podem ser responsáveis pela associação do QTL com a deposição de gordura na carcaça em galinhas. / Eighteen chickens from a parental generation used in a reciprocal cross with broiler and layer lines were sequenced by new generation technology with an average of 10-fold coverage. The DNA sequencing was performed by Illumina next generation platform. The genetic variants discovery was performed in a quantitative trait loci (QTL) region which was previously associated with abdominal fat weight and percentage in chicken chromosome 3 (GGA3) between the microsatellite markers LEI0161 and ADL0371 (33,595,706-42,632,651 bp). SAMtools software was used to detect 136,054 unique SNPs and 15,496 unique INDELs for the 18 chickens, and after quality filtration 92,518 unique SNPs and 9,298 unique INDELs were retained. One list of 77 genes was analised and genes related to lipid metabolism were searched. Variants located in coding region (386 SNPs and 15 INDELs) were identified and associated with important metabolic pathways. Loss of functional variants in the genes LOC771163, EGLN1, GNPAT, FAM120B, THBS2 and GGPS1 may be responsible for the QTL associated with fat deposition in chicken.

A produção brasileira de carne de frango tem uma grande importância econômica no mundo todo devido principalmente aos avanços do melhoramento genético. O surgimento de novas tecnologias de sequenciamento (sequenciamento de nova geração) tem se tornado uma ferramenta poderosa, pois por meio da identificação de SNPs (polimorfismo de nucleotídeo único) e INDELs (deleções/inserções) possibilita a adição de novas informações ao melhoramento genético. A deposição de músculo, em especial o músculo de peito, é uma das características que mais merecem destaque por causa da sua importância nutricional e econômica. Sendo assim o objetivo deste trabalho foi ressequenciar o genoma de 18 aves de duas linhagens distintas experimentais e identificar SNPs e INDELs em uma região de QTL no cromossomo 2 da galinha associado anteriormente com deposição de músculo do peito, além de caracterizar variantes potencialemente funcionais e propor mutações candidatas para estudos futuros. Para isso, dezoito galinhas de duas diferentes linhagens experimentais (corte e postura), ambas desenvolvidas pela Embrapa Suíno e Aves, foram sequenciadas pela plataforma de nova geração da Illumina. SNPs e INDELs foram identificados por meio de ferramentas de bioinformática em uma região de QTL no cromossomo 2 da galinha (105.848.755-112.648.761 pb) que foi previamente associada com deposição de músculo de peito. O sequenciamento dos 18 animais gerou em torno 2,7 bilhões de reads e após a filtragem por qualidade foram mantidas 77% das reads. Em seguida, as reads foram alinhadas ao genoma referência (Gallus_gallus-4.0, NCBI) pela ferramenta Bowtie2 e gerou em média 10,6X de cobertura de sequenciamento na região-alvo. , Foram identificados 722.832 SNPs e 63.727 INDELs para os 18 animais por meio do programa SAMtools, e após uma filtragem rigorosa, foram mantidos 77% dos SNPs (n=558.767) e 60% das INDELs (n=38.402). Com base nas variantes únicas para os 18 animais (85.765 SNPs e 7.824 INDELs) foi realizada a anotação funcional por meio da ferramenta ANNOVAR. Dentre os SNPs não sinônimos (n=153) e stopgain (n=3), 15 foram classificados como deletérios. Um dos SNPs deletérios que já foi depositado em banco de dados foi identificado no gene RB1CC1, que tem sua função relacionada ao desenvolvimento do músculo de peito. Utilizando a ferramenta DAVID foi possível analisar 37 genes relacionados aos SNPs não sinônimos, stopgain, INDELs frameshift e não frameshift. Dentre estes genes, três (DTNA, RB1CC1 e C-MOS) foram selecionados por terem suas funções relacionadas ao desenvolvimento muscular e suas mutações foram analisadas. Sendo assim, futuros estudos podem ser realizados nestes genes candidatos e nas mutações identificadas, por meio de análises de associação e validação em populações comerciais, permitindo assim uma melhor explicação o efeito do QTL estudado. / The Brazilian chicken meat production has a great economic importance in worldwide mainly due to advances in breeding. The emergence of new techniques of sequencing (nextgeneration sequencing) becomes a powerful tool because through identification of SNPs (single nucleotide polymorphism) and INDELs (deletions/insertions) allows the addition of new information for genetic improvement. The muscle deposition, particularly the breast muscle, is one of the features that are most noteworthy because of its nutritional and economic importance. Therefore the aim of this study was to perform the genome resequencing of 18 chicken from two distinct experimental lines and identify SNPs and INDELs in a QTL region on chromosome 2 previously associated with breast muscle, and characterize the variants to identify potentially function ones and propose candidate mutations for future studies. To achieve these objectives, eighteen chickens of two different experimental lines (broiler and layer), both developed by Embrapa Swine and Poultry were sequenced by Illumina next-generation platform. SNPs and INDELs were identified by bioinformatic tools in a QTL region on chicken chromosome 2 (105,848,755-112,648,761 bp) which was previously associated with breast muscle deposition. Sequencing of the eighteen animals generated around 2.7 billion of reads, and 77% of the reads were retained after filtering. The reads were aligned against the chicken genome reference (Gallus_gallus-4.0, NCBI) by Bowtie2 tool resulting in a 10.6X coverage across the target region. Using SAMtools, 722,832 SNPs and 63,727 INDELs were identified in the all individuals, and after a stringent filtration, 77% of SNPs (n=558,767) and 60% of INDELs (n=38,402) were maintained. Based on unique variants for all the animal (85,765 SNPs and 7,828 INDELs) were performed the functional annotation by ANNOVAR tool. Among the non-synonymous SNPs (n=153) and stopgain (n=3), fifteen were predicted like a deleterious mutation. One of deleterious SNPs has already deposited in public database, and it was identified in RB1CC1 gene, which function is related to breast muscle development. Using the DAVID tool was possible to analyze the 37 genes related to the non-synonymous SNPs, stopgain, frameshift and non-frameshift INDELs. Among these genes, three (DTNA, RB1CC1 and C-MOS) were selected due their functions related to muscle development and their mutations were analyzed. Therefore, further association studies can be performed with these candidate genes and their mutations, and also validation in commercial populations, allowing a better explanation of QTL effects.

A produção brasileira de carne de frango tem uma grande importância econômica no mundo todo devido principalmente aos avanços do melhoramento genético. O surgimento de novas tecnologias de sequenciamento (sequenciamento de nova geração) tem se tornado uma ferramenta poderosa, pois por meio da identificação de SNPs (polimorfismo de nucleotídeo único) e INDELs (deleções/inserções) possibilita a adição de novas informações ao melhoramento genético. A deposição de músculo, em especial o músculo de peito, é uma das características que mais merecem destaque por causa da sua importância nutricional e econômica. Sendo assim o objetivo deste trabalho foi ressequenciar o genoma de 18 aves de duas linhagens distintas experimentais e identificar SNPs e INDELs em uma região de QTL no cromossomo 2 da galinha associado anteriormente com deposição de músculo do peito, além de caracterizar variantes potencialemente funcionais e propor mutações candidatas para estudos futuros. Para isso, dezoito galinhas de duas diferentes linhagens experimentais (corte e postura), ambas desenvolvidas pela Embrapa Suíno e Aves, foram sequenciadas pela plataforma de nova geração da Illumina. SNPs e INDELs foram identificados por meio de ferramentas de bioinformática em uma região de QTL no cromossomo 2 da galinha (105.848.755-112.648.761 pb) que foi previamente associada com deposição de músculo de peito. O sequenciamento dos 18 animais gerou em torno 2,7 bilhões de reads e após a filtragem por qualidade foram mantidas 77% das reads. Em seguida, as reads foram alinhadas ao genoma referência (Gallus_gallus-4.0, NCBI) pela ferramenta Bowtie2 e gerou em média 10,6X de cobertura de sequenciamento na região-alvo. , Foram identificados 722.832 SNPs e 63.727 INDELs para os 18 animais por meio do programa SAMtools, e após uma filtragem rigorosa, foram mantidos 77% dos SNPs (n=558.767) e 60% das INDELs (n=38.402). Com base nas variantes únicas para os 18 animais (85.765 SNPs e 7.824 INDELs) foi realizada a anotação funcional por meio da ferramenta ANNOVAR. Dentre os SNPs não sinônimos (n=153) e stopgain (n=3), 15 foram classificados como deletérios. Um dos SNPs deletérios que já foi depositado em banco de dados foi identificado no gene RB1CC1, que tem sua função relacionada ao desenvolvimento do músculo de peito. Utilizando a ferramenta DAVID foi possível analisar 37 genes relacionados aos SNPs não sinônimos, stopgain, INDELs frameshift e não frameshift. Dentre estes genes, três (DTNA, RB1CC1 e C-MOS) foram selecionados por terem suas funções relacionadas ao desenvolvimento muscular e suas mutações foram analisadas. Sendo assim, futuros estudos podem ser realizados nestes genes candidatos e nas mutações identificadas, por meio de análises de associação e validação em populações comerciais, permitindo assim uma melhor explicação o efeito do QTL estudado. / The Brazilian chicken meat production has a great economic importance in worldwide mainly due to advances in breeding. The emergence of new techniques of sequencing (nextgeneration sequencing) becomes a powerful tool because through identification of SNPs (single nucleotide polymorphism) and INDELs (deletions/insertions) allows the addition of new information for genetic improvement. The muscle deposition, particularly the breast muscle, is one of the features that are most noteworthy because of its nutritional and economic importance. Therefore the aim of this study was to perform the genome resequencing of 18 chicken from two distinct experimental lines and identify SNPs and INDELs in a QTL region on chromosome 2 previously associated with breast muscle, and characterize the variants to identify potentially function ones and propose candidate mutations for future studies. To achieve these objectives, eighteen chickens of two different experimental lines (broiler and layer), both developed by Embrapa Swine and Poultry were sequenced by Illumina next-generation platform. SNPs and INDELs were identified by bioinformatic tools in a QTL region on chicken chromosome 2 (105,848,755-112,648,761 bp) which was previously associated with breast muscle deposition. Sequencing of the eighteen animals generated around 2.7 billion of reads, and 77% of the reads were retained after filtering. The reads were aligned against the chicken genome reference (Gallus_gallus-4.0, NCBI) by Bowtie2 tool resulting in a 10.6X coverage across the target region. Using SAMtools, 722,832 SNPs and 63,727 INDELs were identified in the all individuals, and after a stringent filtration, 77% of SNPs (n=558,767) and 60% of INDELs (n=38,402) were maintained. Based on unique variants for all the animal (85,765 SNPs and 7,828 INDELs) were performed the functional annotation by ANNOVAR tool. Among the non-synonymous SNPs (n=153) and stopgain (n=3), fifteen were predicted like a deleterious mutation. One of deleterious SNPs has already deposited in public database, and it was identified in RB1CC1 gene, which function is related to breast muscle development. Using the DAVID tool was possible to analyze the 37 genes related to the non-synonymous SNPs, stopgain, frameshift and non-frameshift INDELs. Among these genes, three (DTNA, RB1CC1 and C-MOS) were selected due their functions related to muscle development and their mutations were analyzed. Therefore, further association studies can be performed with these candidate genes and their mutations, and also validation in commercial populations, allowing a better explanation of QTL effects.

Dezoito galinhas de uma população experimental utilizada em um cruzamento recíproco entre as linhagens de frangos de corte (TT) e de postura (CC) foram sequenciadas pela tecnologia de nova geração na plataforma Illumina com uma cobertura média de 10X. A descoberta de variantes genéticas foi realizada em uma região de locos de característica quantitativa (Quantitative Trait Locus, QTL), associado anteriormente com peso e percentagem de gordura abdominal no cromossomo 3 da galinha (GGA3), entre os marcadores microssatélites LEI0161 e ADL0371 (33,595,706-42,632,651 pb). O programa SAMtools foi utilizado na identificação de 136.054 SNPs únicos e 15.496 INDELs únicas nos 18 animais sequenciados e após a filtragem das mutações, 92.518 SNPs únicos e 9.298 INDELs únicas foram mantidas. Uma lista de 77 genes foi analisada buscando genes relacionados ao metabolismo de lipídios. Variantes localizadas na região codificante (386 SNPs e 15 INDELs) foram identificadas e associadas com vias metabólicas importantes. Variantes nos genes LOC771163, EGLN1, GNPAT, FAM120B, THBS2 e GGPS1 foram identificadas e podem ser responsáveis pela associação do QTL com a deposição de gordura na carcaça em galinhas. / Eighteen chickens from a parental generation used in a reciprocal cross with broiler and layer lines were sequenced by new generation technology with an average of 10-fold coverage. The DNA sequencing was performed by Illumina next generation platform. The genetic variants discovery was performed in a quantitative trait loci (QTL) region which was previously associated with abdominal fat weight and percentage in chicken chromosome 3 (GGA3) between the microsatellite markers LEI0161 and ADL0371 (33,595,706-42,632,651 bp). SAMtools software was used to detect 136,054 unique SNPs and 15,496 unique INDELs for the 18 chickens, and after quality filtration 92,518 unique SNPs and 9,298 unique INDELs were retained. One list of 77 genes was analised and genes related to lipid metabolism were searched. Variants located in coding region (386 SNPs and 15 INDELs) were identified and associated with important metabolic pathways. Loss of functional variants in the genes LOC771163, EGLN1, GNPAT, FAM120B, THBS2 and GGPS1 may be responsible for the QTL associated with fat deposition in chicken.

Insertions/deletions (indels) are potentially powerful evolutionary markers, but little is known about their evolution and few tools exist to effectively study them. To address this, I developed SeqFIRE, a tool for automated identification and extraction of indels from protein multiple sequence alignments. The program also extracts conserved alignment blocks, thus covering all major steps in preparing multiple sequence alignments for phylogenetic analysis. I then used SeqFIRE to build an indel database, using 299 single copy proteins from a broad taxonomic sampling of mainly multicellular eukaryotes. A total of 4,707 indels were extracted, of which 901 are simple (one genetic event) and 3,806 are complex (multiple events). The most abundant indels are single amino acid simple indels. Indel frequency decreases exponentially with length and shows a linear relationship with host protein size. Singleton indels reveal a strong bias towards insertions (2.31 x deletions on average). These analyses also identify 43 indels marking major clades in Plantae and Fungi (clade defining indels or CDIs), but none for Metazoa. In order to study the 3806 complex indels they were first classified by number of states. Analysis of the 2-state complex and simple indels combined (“bi-state indels”) confirms that insertions are over 2.5 times as frequent as deletions. Three-quarters of the complex indels had three-nine states (“slightly complex indels”). A tree-assisted search method was developed allowing me to identify 1,010 potential CDIs supporting all examined major branches of Plantae and Fungi. Forty-two proteins were also found to host complex indel CDIs for the deepest branches of Metazoa. After expanding the taxon set for these proteins, I identified a total of 49 non-bilaterian specific CDIs. Parsimony analysis of these indels places Ctenophora as sister taxon to all other Metazoa including Porifera. Six CDIs were also found placing Placozoa as sister to Bilateria. I conclude that slightly complex indels are a rich source of CDIs, and my tree-assisted search strategy could be automated and implemented in the program SeqFIRE to facilitate their discovery. This will have important implications for mining the phylogenomic content of the vast resource of protist genome data soon to become available.

Insertion and deletion (indel), a common form of genetic variation, has been shown to cause or contribute to human genetic diseases and cancer. Despite this importance and being the second most abundant variant type in the human genome, indels have not been studied as much as the single nucleotide polymorphism (SNP). With the advance of next-generation sequencing technology, many indel calling tools have been developed. However, performance comparison of commonly used tools has shown that (1) the tools have limited power in identifying indels and there are significant number of indels undetected, and (2) there is significant disagreement among the indel sets produced by the tools. These findings indicate the necessity of improving the existing tools or developing new algorithms to achieve reliable and consistent indel calling results. Two indels are biologically equivalent if the resulting sequences are the same. Storing biologically equivalent indels as distinct entries in databases causes data redundancy and misleads downstream analysis. It is thus desirable to have a unified system for identifying and representing equivalent indels. This dissertation describes UPS-indel, a utility tool that creates a universal positioning system for indels so that equivalent indels can be uniquely determined by their coordinates in the new system. Results show that UPS-indel identifies more redundant indels than existing algorithms. While mapping short reads to the reference genome, a significant number of short reads are unmapped and excluded from downstream analyses, thereby causing information loss in the subsequent variant calling. This dissertation describes Genesis-indel, a computational pipeline that explores the unmapped reads to identify missing novel indels. Results analyzing sequence alignment of 30 breast cancer patients show that Genesis-indel identifies many novel indels that also show significant enrichment in oncogenes and tumor suppressor genes, demonstrating the importance of rescuing indels hidden in the unmapped reads in cancer and disease studies. Somatic mutations play a vital role in transforming healthy cells into cancer cells. Therefore, accurate identification of somatic mutations is essential. Many somatic mutations callers are available with different strengths and weaknesses. An ensemble approach integrating the power of the callers is warranted. This dissertation describes SomaticHunter, an ensemble of two callers, namely Platypus and VarDict. Results on synthetic tumor data show that for both SNPs and indels, SomaticHunter achieves recall comparable to the state-of-the-art somatic mutation callers and the highest precision, resulting in the highest F1 score. / Doctor of Philosophy / Insertion and deletion (indel), a common form of genetic variation in the human genome, is associated with genetic diseases and cancer. However, indels are heavily understudied due to experimental and computational challenges. This dissertation addresses the computational challenges in three aspects. First, the current approach of representing indels is ambiguous and causes significant database redundancy. A universal positioning system, UPS-indel, is proposed to represent equivalent indels unambiguously and the UPS-indel algorithm is theoretically proven to find all equivalent indels and is thus exhaustive. Second, a significant number of indels are hidden in DNA reads not mapped to the reference genome. Genesis-indel, a computational pipeline that explores the unmapped reads to identify novel indels that are initially missed, is developed. Genesis-indel has been shown to uncover indels that can be important genetic markers for breast cancer. Finally, mutations occurring in somatic cells play a vital role in transforming healthy cells into cancer cells. Therefore, accurate identification of somatic mutation is essential for a better understanding of cancer genomes. SomaticHunter, an ensemble of two sensitive variant callers, is developed. Simulated studies using whole genome and whole exome sequences have shown that SomaticHunter achieves recall comparable to state-of-the-art somatic mutation callers while delivering the highest precision and therefore resulting in the highest F1 score among all the callers compared.

Polimorfismos do tipo indel são os mais abundantes depois dos SNPs, representando 3,6 milhões das variantes caracterizadas pelo projeto 1000 Genomes. Com uma distribuição que pode ser estimada em mais de um indel a cada 1000 pb, são facilmente encontrados em regiões de interesse. A baixa taxa de mutação e a possibilidade de desenhar primers alelo-específicos são as principais características dos indels que os diferenciam de STRs. O uso de primers aleloespecíficos na detecção e dosagem de misturas de DNA apresenta maior sensibilidade e acurácia que as técnicas usualmente empregadas. Aqui foram descritos, para 10 lócus indel, pares de primers flanqueadores e alelo-específicos para ambos os alelos (inserção e deleção) e foi realizado o estudo populacional em 160 indivíduos. A determinação de fenótipos e avaliação de especificidade dos primers, dos quais 28 foram específicos, foi realizada por PCR convencional seguida de PAGE. As análises populacionais e forenses mostraram que esses lócus apresentam alta variabilidade (heterozigose de 30-50%) e consequentemente, alta informatividade. Os valores de PIC, PE e PD variaram de 0,2763 a 0,3750; 0,1381 a 0,1875 e 0,4978 a 0,6250 respectivamente. Os valores cumulativos de PCE e PCD foram respectivamente 0,8508 e 0,9999. Assim, esse conjunto de indels é indicado para serem testados na detecção e quantificação de misturas de DNA a partir da amplificação alelo-específica. / Indels polymorphisms are the most abundant after SNPs, representing 3.6 million of the variants characterized by the 1000 Genomes project. With a distribution that can be estimated at more than one indel per 1000 bp, they are easily found in regions of interest. The low mutation rate and the possibility of designing allele-specific primers are the main characteristics of the indels that differentiate them from STRs. The use of allele-specific primers in the detection and dosage of DNA mixtures is more sensitive and accurate than regularly employed techniques. Here, for 10 indel loci, pairs of flanking primers and allele-specific primers, for both alleles (insertion and deletion), were described and a population study was performed on 160 individuals. Determining phenotypes and evaluation of primers specificity, of which 28 were specific, was performed by conventional PCR followed by PAGE. In population and forensic analysis, these loci showed high variability (heterozygosis of 30-50%) and consequently high informativeness. The values of PIC, PE and PD ranged from 0.2763 to 0.3750, 0.1381 to 0.1875 and 0.49978 to 0.6250 respectively. Combined values of PCE and PCD were respectively 0.8508 and 0.9999. Thus, this set of indels is indicated to be tested for detection and quantification of DNA mixtures using the allele-specific amplification method.