7 research outputs found

    An 8.22 Mb Assembly and Annotation of the Alpaca (Vicugna pacos) Y Chromosome.

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    The unique evolutionary dynamics and complex structure make the Y chromosome the most diverse and least understood region in the mammalian genome, despite its undisputable role in sex determination, development, and male fertility. Here we present the first contig-level annotated draft assembly for the alpaca (Vicugna pacos) Y chromosome based on hybrid assembly of short- and long-read sequence data of flow-sorted Y. The latter was also used for cDNA selection providing Y-enriched testis transcriptome for annotation. The final assembly of 8.22 Mb comprised 4.5 Mb of male specific Y (MSY) and 3.7 Mb of the pseudoautosomal region. In MSY, we annotated 15 X-degenerate genes and two novel transcripts, but no transposed sequences. Two MSY genes, HSFY and RBMY, are multicopy. The pseudoautosomal boundary is located between SHROOM2 and HSFY. Comparative analysis shows that the small and cytogenetically distinct alpaca Y shares most of MSY sequences with the larger dromedary and Bactrian camel Y chromosomes. Most of alpaca X-degenerate genes are also shared with other mammalian MSYs, though WWC3Y is Y-specific only in alpaca/camels and the horse. The partial alpaca Y assembly is a starting point for further expansion and will have applications in the study of camelid populations and male biology

    Identificación de polimorfismos de nucleótido simple y su asociación con el diámetro de fibra en alpacas Huacaya (Vicugna pacos)

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    Universidad Nacional Agraria La Molina. Escuela de Posgrado. Doctorado en Ciencia AnimalEl objetivo de la investigación fue la identificación de polimorfismos de nucleótido simple (PNSs) y su asociación con el diámetro de fibra en alpacas Huacaya. En una primera etapa se genotipificaron muestras de ADN de 40 alpacas Huacaya utilizando una micromatriz de 777,962 PNSs diseñada para bovinos (BovineHD Genotyping Beadchip, Illumina). El análisis de datos incluyó el uso de combinaciones de los parámetros umbral de no determinación (≥ 0.05, ≥ 0.15 y ≥ 0.25) y frecuencia de genotipificación (≥ 0.9 y = 1.0); también se consideraron la puntuación “GenCall” (GC) promedio (≥ 0.70) y la puntuación “GenTrain” (≥ 0.25). Los PNSs con frecuencia alélica menor (FAM) ≥ 0.05 o ≥ 0.01 fueron conservados. Todas las secuencias flanqueantes de PNSs positivos con alineaciones perfectas entre los genomas bovino y de alpaca para los primeros 21 o 26 nucleótidos que flanquean el nucleótido variante en ambos lados fueron seleccionados. Los PNSs localizados en un único andamio fueron considerados únicos. Los PNSs únicos identificados en ambos genomas de referencia se conservaron y mapearon en el genoma de Vicugna_pacos-2.0.2. El uso del umbral de no determinación ≥ 0.25, frecuencia de genotipificación = 1 y puntuación GC promedio ≥ 0.7 resultó en el menor número de PNSs identificados (6,756 PNSs), de los cuales 400 eran únicos y polimórficos (FAM ≥ 0.01). La asignación a los cromosomas de alpaca fue posible para 292 PNSs. Asimismo, 209 PNSs se localizaron en 202 loci de genes de alpaca. En una segunda etapa se colectaron muestras de ADN de 881 alpacas Huacaya hembras de color blanco procedentes de dos regiones geográficas andinas, considerando tres rebaños de alpacas dentro de cada región. Las muestras se genotipificaron utilizando una micromatriz de 76,508 PNSs, diseñada para alpacas (Affymetrix Custom Alpaca genotyping array). Se desarrollaron dos controles de calidad utilizando los programas Axiom Analysis Suite v.4.0.3.3 y PLINK v1.90p. Se realizaron cuatro métodos de estudio de asociación del genoma completo (GWAS, por sus siglas en inglés): (i) GWAS basado en un modelo lineal, (ii) Análisis de haplotipos y marcadores, (iii) GWAS con descomposición de autovectores (EigenGWAS) y (iv) Señales de selección basadas en homocigosidad de haplotipo extendido entre poblaciones (XP-EHH, por sus siglas en inglés). Después del primer control de calidad, se conservaron 861 muestras y 69,685 PNSs. Luego del segundo control de calidad, se retuvo un total de 61,814 PNSs, ubicados en 1,838 andamios. De14 acuerdo con cada método se identificaron: (i) 39 PNSs no significativos con p-value menor a 1 x 10-4, (ii) once haplotipos con una heredabilidad estandarizada superior a 6 desviaciones estándar, (iii) 50 PNSs con p-value corregido menor a 8.09 x 10-7, (iv) 217 PNSs con valores estandarizados de XP-EHH superiores a |3|. Se identificaron 337 PNSs distribuidos en 149 regiones, de las cuales 53 regiones se encuentran formadas por dos o más PNSs separados a una distancia máxima de 500 kbp. Las anotaciones Gene Ontology (GO) de estos genes incluyeron la morfogénesis del folículo piloso (BCL2, SOSTDC1, WNT10A), el desarrollo del folículo piloso (EDA, TNFRSF19, WNT10A) y el desarrollo de la piel (ABCB6, EDA, WNT10A). Cuatro regiones candidatas con PNSs adyacentes identificados por dos métodos se ubicaron en los cromosomas VPA2, VPA5, VPA18 y VPA26. PNSs significativos localizados en los cromosomas VPA5, VPA18 y VPA27 fueron localizados dentro o cercano a genes reportados en cabras para características de fibra, y podrían ser considerados como PNSs candidatos. Este es el primer estudio de asociación del genoma completo con el diámetro de fibra en alpacas Huacaya, utilizando una micromatriz de PNSs diseñada para alpacas.The aim of the research was the identification of single nucleotide polymorphisms (SNPs) and their association with fiber diameter in Huacaya alpacas. In a first stage, DNA samples from 40 Huacaya alpacas were genotyped using a 777,962 SNPs microarray designed for cattle (BovineHD Genotyping Beadchip, Illumina). The data analysis included the use of combinations of the threshold parameters of no-call threshold (≥0.05, ≥0.15, and ≥0.25) and call frequency (≥0.9 and =1.0); Average GenCall (GC) score (≥0.70) and GenTrain score (≥0.25) were also considered. SNPs with minor allele frequency (MAF) ≥ 0.05 or ≥ 0.01 were retained. All positive SNP flanking sequences showing perfect alignments between the bovine and alpaca genomes for the first 21 or 26 nucleotides flanking the variant nucleotide at either side were selected. Only SNPs localized in one scaffold were assumed unique. Unique SNPs identified in both reference genomes were kept and mapped on the Vicugna_pacos-2.0.2 genome. The use of the no-call threshold ≥ 0.25, call frequency = 1 and average GC score ≥ 0.7 resulted in the lowest number of SNPs identified (6,756 SNPs), of which 400 were unique and polymorphic (MAF ≥ 0.01). Assignment to alpaca chromosomes was possible for 292 SNPs. Likewise, 209 SNPs were localized in 202 alpaca gene loci. In a second stage, DNA samples were collected from 881 female Huacaya alpacas from two geographical Andean regions, considering three herds of alpacas within each region. The samples were genotyped using a microarray of 76,508 SNPs, designed for alpacas (Affymetrix Custom Alpaca genotyping array). Two quality controls were developed using Axiom Analysis Suite v.4.0.3.3 and PLINK v1.90p. Four genome wide association study (GWAS) methods were performed: (i) GWAS based on a linear model, (ii) Haplotype and marker analysis, (iii) GWAS with eigenvector decomposition (EigenGWAS) and (iv) Selection signatures based on Cross Population Extended Haplotype Homozygosity (XP-EHH). After the first quality control, 861 samples and 69,685 SNPs were selected. After the second quality control, a total of 61,814 SNPs, localized on 1,838 scaffolds, were retained. According to each method: (i) 39 not significant SNPs with p-value less than 1 x 10-4, (ii) eleven haplotypes with standardized haplotype heritability higher than 6 standard deviations, (iii) 50 SNPs with corrected p-value less than 8.09 x 10-7, (iv) 217 SNPs with standardized XP-EHH values greater than |3|, were identified. A set of 337 SNPs distributed16 in 149 regions were identified, of which 53 regions are formed by two or more SNPs separated at a maximum distance of 500 kbp. Gene Ontology (GO) annotations of these genes included hair follicle morphogenesis (BCL2, SOSTDC1, WNT10A), hair follicle development (EDA, TNFRSF19, WNT10A) and skin development (ABCB6, EDA, WNT10A). Four candidate regions with adjacent SNPs identified by two methods were located on chromosomes VPA2, VPA5, VPA18 and VPA26. Significant SNPs localized on chromosomes VPA5, VPA18 and VPA27 were localized within o close to genes reported in goats for fiber traits, and could be considered candidate SNPs. This study represents the first alpaca genome wide association study for fiber diameter in Huacaya alpacas, using a SNP microarray designed for alpacas

    An 8.22 Mb Assembly and Annotation of the Alpaca (Vicugna pacos) Y Chromosome

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    The unique evolutionary dynamics and complex structure make the Y chromosome the most diverse and least understood region in the mammalian genome, despite its undisputable role in sex determination, development, and male fertility. Here we present the first contig-level annotated draft assembly for the alpaca (Vicugna pacos) Y chromosome based on hybrid assembly of short- and long-read sequence data of flow-sorted Y. The latter was also used for cDNA selection providing Y-enriched testis transcriptome for annotation. The final assembly of 8.22 Mb comprised 4.5 Mb of male specific Y (MSY) and 3.7 Mb of the pseudoautosomal region. In MSY, we annotated 15 X-degenerate genes and two novel transcripts, but no transposed sequences. Two MSY genes, HSFY and RBMY, are multicopy. The pseudoautosomal boundary is located between SHROOM2 and HSFY. Comparative analysis shows that the small and cytogenetically distinct alpaca Y shares most of MSY sequences with the larger dromedary and Bactrian camel Y chromosomes. Most of alpaca X-degenerate genes are also shared with other mammalian MSYs, though WWC3Y is Y-specific only in alpaca/camels and the horse. The partial alpaca Y assembly is a starting point for further expansion and will have applications in the study of camelid populations and male biology

    Genome editing approaches for development of pan-population immunotherapies

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    Background - T-cell based immunotherapy is the greatest recent breakthrough in cancer treatment, and can induce complete lasting remission. T-cells are capable of responding to a vast diversity of antigens via their hypervariable T-cell receptor (TCR). However, current immunotherapies rely on αβ T-cells which are restricted to person-specific Human Leukocyte Antigen (HLA) molecules presenting peptides from cancer-specific antigens. Thus, a given αβ TCR therapy is applicable only to a minority of patients. In contrast, γδ T-cells, and some αβ T-cells, recognise diverse cancer types regardless of the HLA type. The aims of my thesis were to investigate the potential of using non-HLA restricted T-cells and their receptors for cancer immunotherapy, and to develop tools to facilitate the study of non-HLA restricted T-cells for cancer treatment. Results – Initially, I developed a CRISPR/Cas9 method for generation of superior TCR transduced cells, in terms of their anticancer reactivity and antigen sensitivity, in comparison to TCR transduced cells generated by current clinical methodologies. Using this TCR replacement method I demonstrated that the anticancer reactivity of broadly cancer-reactive γδ T-cells derived from a variety of clinically relevant sources is dependent on their TCRs. I also used CRISPR/Cas9 genome editing to generate a panel of cancer cell lines deficient in known ligands of non-HLA restricted T-cells that can be used for initial dissection of their anticancer reactivity. Using this approach, I demonstrated that one of non-HLA restricted T-cell clones I procured recognised targets via CD1a. Finally, I developed a whole genome CRISPR/Cas9 pipeline for discovery of ligands and pathways essential for cancer cell recognition by non-HLA restricted T-cells. Conclusions – My research demonstrated that TCRs from broadly cancer-reactive T-cells can be used to re-direct primary T-cells to many cancer types regardless of their HLA type, paving the way for pan-population immunotherapy. The discovery of non-HLA ligands for broadly cancer-reactive T-cells can be achieved using whole genome and targeted CRISPR/Cas9 gene editing technology
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