Performance Evaluation of Highly Admixed Tanzanian Smallholder Dairy Cattle Using SNP Derived Kinship Matrix

A novel 193-plex MPS panel integrating STRs and SNPs highlights the application value of forensic genetics in individual identification and paternity testing

Massively parallel sequencing (MPS) has emerged as a promising technology for targeting multiple genetic loci simultaneously in forensic genetics. Here, a novel 193-plex panel was designed to target 28 A-STRs, 41 Y-STRs, 21 X-STRs, 3 sex-identified loci, and 100 A-SNPs by employing a single-end 400 bp sequencing strategy on the MGISEQ-2000™ platform. In the present study, a series of validations and sequencing of 1642 population samples were performed to evaluate the overall performance of the MPS-based panel and its practicality in forensic application according to the SWGDAM guidelines. In general, the 193-plex markers in our panel showed good performance in terms of species specificity, stability, and repeatability. Compared to commercial kits, this panel achieved 100% concordance for standard gDNA and 99.87% concordance for 14,560 population genotypes. Moreover, this panel detected 100% of the loci from 0.5 ng of DNA template and all unique alleles at a 1:4 DNA mixture ratio (0.2 ng minor contributor), and the applicability of the proposed approach for tracing and degrading DNA was further supported by case samples. In addition, several forensic parameters of STRs and SNPs were calculated in a population study. High CPE and CPD values greater than 0.9999999 were clearly demonstrated and these results could be useful references for the application of this panel in individual identification and paternity testing. Overall, this 193-plex MPS panel has been shown to be a reliable, repeatable, robust, inexpensive, and powerful tool sufficient for forensic practice.

Potential for quantifying general environmental resilience of dairy cattle in sub-Saharan Africa using deviations in milk yield

Introduction: Genetic improvement of general resilience of dairy cattle is deemed as a part of the solution to low dairy productivity and poor cattle adaptability in sub-Saharan Africa (SSA). While indicators of general resilience have been proposed and evaluated in other regions, their applicability in SSA remains unexplored. This study sought to test the viability of utilizing log-transformed variance (LnVar), autocorrelation (rauto), and skewness (Skew) of deviations in milk yield as indicators of general resilience of dairy cows performing in the tropical environment of Kenya. Methods: Test-day milk yield records of 2,670 first-parity cows performing in three distinct agroecological zones of Kenya were used. To predict expected milk yield, quantile regression was used to model lactation curve for each cow. Subsequently, resilience indicators were defined based on actual and standardized deviations of observed milk yield from the expected milk yield. The genetic parameters of these indicators were estimated, and their associations with longevity and average test-day milk yield were examined. Results: All indicators were heritable except skewness of actual and standardized deviation. The log-transformed variance of actual (LnVar1) and standardized (LnVar2) deviations had the highest heritabilities of 0.19 ± 0.04 and 0.17 ± 0.04, respectively. Auto-correlation of actual (rauto1) and standardized (rauto2) deviations had heritabilities of 0.05 ± 0.03 and 0.07 ± 0.03, respectively. Weak to moderate genetic correlations were observed among resilience indicators. Both rauto and Skew indicators had negligible genetic correlations with both longevity and average test-day milk yield. LnVar1 and LnVar2 were genetically associated with better longevity (rg = -0.47 ± 0.26 and -0.49 ± 0.26, respectively). Whereas LnVar1 suggested that resilient animals produce lower average test-day milk yield, LnVar2 revealed a genetic association between resilience and higher average test-day milk yield. Discussion: Log transformed variance of deviations in milk yield holds a significant potential as a robust resilience indicator for dairy animals performing in SSA. Moreover, standardized as opposed to actual deviations should be employed in defining resilience indicators because the resultant indicator does not inaccurately infer that low-producing animals are inherently resilient. This study offers an opportunity for enhancing the productivity of dairy cattle performing in SSA through selective breeding for resilience to environmental stressors.

Exploration of biomarkers for the diagnosis, treatment and prognosis of cervical cancer: a review

As the fourth most diagnosed cancer, cervical cancer (CC) is one of the major causes of cancer-related mortality affecting females globally, particularly when diagnosed at advanced stage. Discoveries of CC biomarkers pave the road to precision medicine for better patient outcomes. High throughput omics technologies, characterized by big data production further accelerate the process. To date, various CC biomarkers have been discovered through the advancement in technologies. Despite, very few have successfully translated into clinical practice due to the paucity of validation through large scale clinical studies. While vast amounts of data are generated by the omics technologies, challenges arise in identifying the clinically relevant data for translational research as analyses of single-level omics approaches rarely provide causal relations. Integrative multi-omics approaches across different levels of cellular function enable better comprehension of the fundamental biology of CC by highlighting the interrelationships of the involved biomolecules and their function, aiding in identification of novel integrated biomarker profile for precision medicine. Establishment of a worldwide Early Detection Research Network (EDRN) system helps accelerating the pace of biomarker translation. To fill the research gap, we review the recent research progress on CC biomarker development from the application of high throughput omics technologies with sections covering genomics, transcriptomics, proteomics, and metabolomics.

Pairwise kinship analysis of 17 pedigrees using massively parallel sequencing

With the tremendous development of massively parallel sequencing (MPS) in the last decade, it has been widely applied in basic science, clinical diagnostics, microbial genomics, as well as forensic genetics. MPS has lots of advantages that may facilitate the kinship analysis. In this study, 243 Chinese Han individuals from 17 families were involved and sequenced using the ForenSeq™ DNA Signature Prep Kit (Verogen, Inc., San Diego, USA), which provided the sequence information of 27 autosomal STRs (A-STRs), 7 X chromosomal STRs (X-STRs), 24 Y chromosomal STRs (Y-STRs) and 94 identity-informative SNPs (iSNPs). A total of 275 pairs of parent-child, 123 pairs of full siblings, 1 pair of twins, 1 pair of half siblings, 158 pairs of grandparent-grandchild, 222 pairs of uncle/aunt-nephew/niece and 121 pairs of first cousins, as well as 701 pairs of unrelated individuals were identified. Using both likelihood ratio (LR) and identical by state (IBS) methods, the kinship analysis was conducted among these relative and non-relative pairs based on the A-STRs and SNPs. As a result, the ForenSeq Signature Kit could solve the analysis of parent-child (t1 = -4, t2 = 4), full siblings (t1 = -2, t2 = 2) and most second-degree kinships (t1 = -1, t2 = 1) using the LR method. When the IBS method was applied, 123 full sibling pairs had a higher average IBS value than other kinship groups in this study. And the IBS method could play a role in the testing of parent-child and full siblings.

Breeding strategies for improving smallholder dairy cattle productivity in Sub-Saharan Africa

Breeding strategies for smallholder dairy farming systems in Sub-Saharan Africa (SSA) were simulated and evaluated considering cow traits identified as priorities by farmers in different agro-ecological zones. These traits were related to cow milk yield, fertility, temperament, feed intake and disease resistance. The first breeding strategy was based on continuous importation of genetically superior exotic dairy sire semen to SSA and crossing with local females leading to a gradual upgrade of the indigenous population. The second strategy assumed that semen from elite exotic bulls would be imported to SSA and used on indigenous cows to produce F1 animals. Thereafter, elite animals would be selected from within the F1 and each subsequent generation to establish a new synthetic breed. The third strategy was to improve the indigenous population by genetically selecting the best sires available domestically. Results showed positive genetic progress for all breeding goal traits. After 15 generations of selection, the genetic response of the importation strategy exceeded the corresponding genetic response of the synthetic breed strategy by 20%-60%. The former also exceeded the genetic response of the indigenous breed improvement strategy by 43%-75%. Potentially there is an opportunity for breeders to choose an appropriate breeding strategy that fits a specific need of smallholder dairy farmers.