Books received

Jorde, Lynn B.; Bamshad, Mike; Watkins, W. Scott; Zenger, R.; Fraley, Alexander E.; Krakowiak, Patrycja A.; Carpenter, Karen; Soodyall, Himla; Jenkins, Trefor; Rogers, Alan R.

doi:10.1002/ajmg.1320570340

Cited by 149 publications

(11 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The degree of interpopulational differentiation (G ST ∼ 10%) for the four South American regions is similar to the values obtained by analyses of nuclear genes, variable number of tandem repeats and RFLPs in Asian, European and American populations [29, 54, 55, 56, 57]. …”

Section: Resultssupporting

confidence: 53%

Genetic Diversity in an Andean Population from Peru and Regional Migration Patterns of Amerindians in South America: Data from Y Chromosome and Mitochondrial DNA

Rodríguez-Delfín

Rubin-de-Celis

Zago³

2000

Hum Hered

View full text Add to dashboard Cite

The genetic variability of a Quechua-speaking Andean population from Peru was examined on the basis of four Y chromosome markers and restriction sites that define the Amerindian mitochondrial DNA (mtDNA) haplogroups. Forty-nine out of 52 (90.4%) individuals had mtDNA which belonged to one of the four common Amerindian haplogroups, with 54% of the samples belonging to haplogroup B. Among 25 males, 12 had an Amerindian Y chromosome, which exists as four haplotypes defined on the basis of the DYS287, DYS199, DYS392 and DYS19 markers, three of which are shared by Amazonian Amerindians. Thus, there is a clear directionality of marriages, with an estimated genetic admixture with non-Amerindians that is 9 times lower for mtDNA than for Y chromosome DNA. The comparison of mtDNA of Andean Amerindians with that of people from other regions of South America in a total of 1,086 individuals demonstrates a geographical pattern, with a decreasing frequency of A and C haplotypes and increasing frequency of the D haplotype from the north of the Amazon River to the south of the Amazon River, reaching the lowest and the highest frequencies, respectively, in the more southern populations of Chile and Argentina. Conversely, the highest and lowest frequencies of the haplogroup B are found, respectively, in the Andean and the North Amazon regions, and it is absent from some southern populations, suggesting that haplotypes A, C and D, and haplotype B may have been dispersed by two different migratory routes within the continent.

show abstract

Section: Resultssupporting

confidence: 53%

Genetic Diversity in an Andean Population from Peru and Regional Migration Patterns of Amerindians in South America: Data from Y Chromosome and Mitochondrial DNA

Rodríguez-Delfín

Rubin-de-Celis

Zago³

2000

Hum Hered

View full text Add to dashboard Cite

show abstract

“…Despite shared Bantu ancestry, compared with other central African Bantu populations we observed a significantly higher frequency of the APOL1 risk alleles in our east African study population with CKD ( Fig 1 ) [23–28]. At the same time, we also observed a significantly lower frequency in our study population compared with other east African Bantu populations, where Trypanasoma brucei rhodesiense is most endemic [13].…”

Section: Discussionsupporting

confidence: 48%

“…In our study population, which consisted predominantly of Chagga individuals of Bantu ancestry, the frequency of APOL1 G1 risk variants was significantly higher than that reported for other Central African Bantu tribes, the Biaka and Mbuti tribes and a non-Bantu Tanzanian tribe, the Sandawe tribe of Khoisan ancestry (p<0.01 for all) ( Table 3 )[23–28]. On the other hand, we observed a significantly lower frequency for the APOL1 G1 risk variants compared with a Kenyan Bantu tribe, the Luhya (p<0.01) and a slightly lower frequency compared with another Tanzanian Bantu tribe, the Zaramo.…”

Section: Resultsmentioning

confidence: 63%

APOL1 risk alleles among individuals with CKD in Northern Tanzania: A pilot study

et al. 2017

View full text Add to dashboard Cite

IntroductionIn sub-Saharan Africa, approximately 100 million people have CKD, yet genetic risk factors are not well-understood. Despite the potential importance of understanding APOL1 risk allele status among individuals with CKD, little genetic research has been conducted. Therefore, we conducted a pilot study evaluating the feasibility of and willingness to participate in genetic research on kidney disease, and we estimated APOL1 risk allele frequencies among individuals with CKD.MethodsIn 2014, we conducted a community-based field study evaluating CKD epidemiology in northern Tanzania. We assessed for CKD using urine albumin and serum creatinine to estimate GFR. We invited participants with CKD to enroll in an additional genetic study. We obtained dried-blood spots on filter cards, from which we extracted DNA using sterile punch biopsies. We genotyped for two single nucleotide polymorphisms (SNPs) defining the APOL1 G1 risk allele and an insertion/deletion polymorphism defining the G2 risk allele. Genotyping was performed in duplicate.ResultsWe enrolled 481 participant, 57 (12%) of whom had CKD. Among these, enrollment for genotyping was high (n = 48; 84%). We extracted a median of 19.4 ng of DNA from each dried-blood spot sample, and we genotyped the two APOL1 G1 SNPs and the APOL1 G2 polymorphism. Genotyping quality was high, with all duplicated samples showing perfect concordance. The frequency of APOL1 risk variants ranged from 7.0% to 11.0%, which was similar to previously-reported frequencies from the general population of northern Tanzania (p>0.2).DiscussionIn individuals with CKD from northern Tanzania, we demonstrated feasibility of genotyping APOL1 risk alleles. We successfully genotyped three risk variants from DNA extracted from filter cards, and we demonstrated a high enrollment for participation. In this population, more extensive genetic studies of kidney disease may be well-received and will be feasible.

show abstract

“…some isozyme studies on fish species) or too small sample sizes. For example, Jorde et al [3]report a phylogenetic analysis of 13 human populations based on 30 tetranucleotide repeat polymorphisms. The sample sizes from some of these populations are as small as 5 individuals (e.g., Biaka Pygmy, Mbuti), whereas the degree of polymorphism at some of the loci (e.g., D19S400, D5S580) ranges from 12 to 22 alleles.…”

Section: Introductionmentioning

confidence: 99%

“…Molecular studies for genetic polymorphisms are being carried out for a number of different applications, such as anthropological and evolutionary studies [1, 2, 3, 4, 5, 6, 7, 8, 9], genetic disorders in different populations [10, 11, 12, 13, 14, 15, 16, 17], pharmacogenomics [18, 19, 20, 21], genetic identification of ethnic groups for forensic and legal applications [22, 23, 24], genetic identification of breed/stock in animals and plants for commercial applications [25]and conservation of germ plasm and applications to crop improvement [26, 27, 28, 29]. In designing these studies, an important issue to be considered is the minimum or optimum size of random sample required so that all the alleles/genotypes at one or more loci are observed with a certain prespecified probability [26, 27, 28, 31]and for reliably estimating allele frequency distributions by statistical methods [31].…”

Section: Introductionmentioning

confidence: 99%

Sample Size Considerations in Genetic Polymorphism Studies

B-Rao¹

2001

Hum Hered

View full text Add to dashboard Cite

Objectives: Molecular studies for genetic polymorphisms are being carried out for a number of different applications, such as genetic disorders in different populations, pharmacogenomics, genetic identification of ethnic groups for forensic and legal applications, genetic identification of breed/stock in animals and plants for commercial applications and conservation of germ plasm. In this paper, for a random sampling scheme, we address two questions: (A) What should be the minimum size of the sample so that, with a prespecified probability, all alleles at a given locus (or haplotypes at a given set of loci) are detected? (B) What should be the sample size so that the allele frequency distribution at a given locus (or haplotype frequency distribution at a given set of loci) is estimated reliably within permissible error limits? Methods: We have used combinatorial probabilistic arguments and Monte Carlo simulations to answer these questions. Results: We found that the minimum sample size required in case A depends mainly on the prespecified probability of detecting all alleles, while in case B, it varies greatly depending on the permissible error in estimation (which will vary with the application). We have obtained the minimum sample sizes for different degrees of polymorphism at a locus under high stringency, as well as a relaxed level of permissible error. We present a detailed sampling procedure for estimating allele frequencies at a given locus, which will be of use in practical applications. Conclusion: Since the sample size required for reliable estimation of allele frequency distribution increases with the number of alleles at the locus, there is a strong case for using biallelic markers (like single nucleotide polymorphisms) when the available sample size is about 800 or less.

show abstract

Books received

Cited by 149 publications

References 32 publications

Genetic Diversity in an Andean Population from Peru and Regional Migration Patterns of Amerindians in South America: Data from Y Chromosome and Mitochondrial DNA

Genetic Diversity in an Andean Population from Peru and Regional Migration Patterns of Amerindians in South America: Data from Y Chromosome and Mitochondrial DNA

APOL1 risk alleles among individuals with CKD in Northern Tanzania: A pilot study

Sample Size Considerations in Genetic Polymorphism Studies

Contact Info

Product

Resources

About