Disentangling river and swamp buffalo genetic diversity: initial insights from the 1000 Buffalo Genomes Project.

More people in the world depend on water buffalo for their livelihoods than on any other domesticated animals, but its genetics is still not extensively explored. The 1000 Buffalo Genomes Project (1000BGP) provides genetic resources for global buffalo population study and tools to breed more sustainable and productive buffaloes. Here we report the most contiguous swamp buffalo genome assembly (PCC_UOA_SB_1v2) with substantial resolution of telomeric and centromeric repeats, ∼4-fold more contiguous than the existing reference river buffalo assembly and exceeding a recently published male swamp buffalo genome. This assembly was used along with the current reference to align 140 water buffalo short-read sequences and produce a public genetic resource with an average of ∼41 million single nucleotide polymorphisms per swamp and river buffalo genome. Comparison of the swamp and river buffalo sequences showed ∼1.5% genetic differences, and estimated divergence time occurred 3.1 million years ago (95% CI, 2.6-4.9). The open science model employed in the 1000BGP provides a key genomic resource and tools for a species with global economic relevance.

Opportunities and Challenges for Improving the Productivity of Swamp Buffaloes in Southeastern Asia.

The swamp buffalo is a domesticated animal commonly found in Southeast Asia. It is a highly valued agricultural animal for smallholders, but the production of this species has unfortunately declined in recent decades due to rising farm mechanization. While swamp buffalo still plays a role in farmland cultivation, this species' purposes has shifted from draft power to meat, milk, and hide production. The current status of swamp buffaloes in Southeast Asia is still understudied compared to its counterparts such as the riverine buffaloes and cattle. This review discusses the background of swamp buffalo, with an emphasis on recent work on this species in Southeast Asia, and associated genetics and genomics work such as cytogenetic studies, phylogeny, domestication and migration, genetic sequences and resources. Recent challenges to realize the potential of this species in the agriculture industry are also discussed. Limited genetic resource for swamp buffalo has called for more genomics work to be done on this species including decoding its genome. As the economy progresses and farm mechanization increases, research and development for swamp buffaloes are focused on enhancing its productivity through understanding the genetics of agriculturally important traits. The use of genomic markers is a powerful tool to efficiently utilize the potential of this animal for food security and animal conservation. Understanding its genetics and retaining and maximizing its adaptability to harsher environments are a strategic move for food security in poorer nations in Southeast Asia in the face of climate change.

Accuracy of Genomic Prediction for Milk Production Traits in Philippine Dairy Buffaloes.

The objective of this study was to compare the accuracies of genomic prediction for milk yield, fat yield, and protein yield from Philippine dairy buffaloes using genomic best linear unbiased prediction (GBLUP) and single-step GBLUP (ssGBLUP) with the accuracies based on pedigree BLUP (pBLUP). To also assess the bias of the prediction, the regression coefficient (slope) of the adjusted phenotypes on the predicted breeding values (BVs) was also calculated. Two data sets were analyzed. The GENO data consisting of all female buffaloes that have both phenotypes and genotypes (n = 904 with 1,773,305-days lactation records) were analyzed using pBLUP and GBLUP. The ALL data, consisting of the GENO data plus females with phenotypes but not genotyped (n = 1,975 with 3,821,305-days lactation records), were analyzed using pBLUP and ssGBLUP. Animals were genotyped with the Affymetrix 90k buffalo genotyping array. After quality control, 60,827 single-nucleotide polymorphisms were used for downward analysis. A pedigree file containing 2,642 animals was used for pBLUP and ssGBLUP. Accuracy of prediction was calculated as the correlation between the predicted BVs of the test set and adjusted phenotypes, which were corrected for fixed effects, divided by the square root of the heritability of the trait, corrected for the number of lactations used in the test set. To assess the bias of the prediction, the regression coefficient (slope) of the adjusted phenotypes on the predicted BVs was also calculated. Results showed that genomic methods (GBLUP and ssGBLUP) provide more accurate predictions compared to pBLUP. Average GBLUP and ssGBLUP accuracies were 0.24 and 0.29, respectively, whereas average pBLUP accuracies (for GENO and ALL data) were 0.21 and 0.22, respectively. Slopes of the two genomic methods were also closer to one, indicating lesser bias, compared to pBLUP. Average GBLUP and ssGBLUP slopes were 0.89 and 0.84, respectively, whereas the average pBLUP (for GENO and ALL data) slopes were 0.80 and 0.54, respectively.

Possible use of RNA isolate from inactivated vaccine for external positive control in reverse transcription-based detection of foot-and-mouth disease virus in bull semen.

This study has demonstrated the novel use of inactivated and purified vaccine against FMD virus for detection and analysis. RNA isolate was efficiently generated from the vaccine for an external positive control for reverse transcription polymerase chain reaction (RT-PCR) and reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays. The target DNA fragment sequences from the 2B region and 3D RNA polymerase gene of the virus for RT-PCR and RT-LAMP respectively were successfully amplified using the RNA template. Laboratories lacking complex equipment may not be feasible to handle high-risk viruses for conventional methods such as the isolation and culture of live viruses. Here, with the use of these molecular tools, novel use of RNA isolate from inactivated, purified vaccine proved to be an effective external positive control for the assays. Therefore, with these methods, the derived RNA control template aids in a safe method for screening FMD virus for diagnostic laboratories. And by using the same technique, it is then possible to generate a standard for diagnosing any other infectious viral diseases.

Convolutional decoding of thermographic images to locate and quantify honey adulterations.

In this research, 56 samples of pure honey have been mixed with different concentrations of rice syrup simulating a set of adulterated samples. A thermographic camera was used to extract data regarding the thermal development of the honey. The resulting infrared images were processed via convolutional neural networks (CNNs), a subset of algorithms within deep learning. The CNNs have been trained and optimized using these images to detect the commonly elusive rice syrup in honey in concentrations as low as 1% in weight, as well as quantify it. Finally, the model was successfully validated using images which were initially isolated from the training database. The result was an algorithm capable of identifying adulterated honey from different floral origins and quantifying rice syrup with accuracies of 95% and 93%, respectively. Therefore, CNNs have complemented the thermographic analysis and have shown to be a compelling tool for the control of food quality, thanks to traits such as high sensitivity, speed, and being independent of highly specialized personnel.

Germline SDHA mutations in children and adults with cancer.

Mutations in succinate dehydrogenase complex genes predispose to familial paraganglioma-pheochromocytoma syndrome (FPG) and gastrointestinal stromal tumors (GIST). Here we describe cancer patients undergoing agnostic germline testing at Memorial Sloan Kettering Cancer Center and found to harbor germline SDHA mutations. Using targeted sequencing covering the cancer census genes, we identified 10 patients with SDHA germline mutations. Cancer diagnoses for these patients carrying SDHA germline mutations included neuroblastoma (n = 1), breast (n = 1), colon (n = 1), renal (n = 1), melanoma and uterine (n = 1), prostate (n = 1), endometrial (n = 1), bladder (n = 1), and gastrointestinal stromal tumor (GIST) (n = 2). Immunohistochemical staining and assessment of patient tumors for second hits and loss of heterozygosity in SDHA confirmed GIST as an SDHA-associated tumor and suggests SDHA germline mutations may be a driver in neuroblastoma tumorigenesis.

Characterization of new founder Alu-mediated rearrangements in MSH2 gene associated with a Lynch syndrome phenotype.

It has been reported that large genomic deletions in the MLH1 and MSH2 genes are a frequent cause of Lynch syndrome in certain populations. Here, a cohort has been screened and two new founder rearrangements have been found in the MSH2 gene. These mutations have been characterized by break point determination, haplotype analysis, and genotype-phenotype correlation. Mutations have been identified in the MLH1, MSH2, and MSH6 genes in 303 subjects from 160 suspected Lynch syndrome unrelated families. All subjects were tested using heteroduplex analysis by capillary array electrophoresis. Multiplex ligation-dependent probe amplification was used to detect rearrangements in mutation-negative index patients and confirmed by reverse transcriptase PCR. The break point of the deletions was further characterized by the array comparative genomic hybridization method. Immunohistochemical staining and microsatellite instability were studied in tumor samples. Hereditary nonpolyposis colorectal cancer-related phenotypes were evaluated. More than 16% (24 of 160) of the families had pathogenic mutations (8 MLH1, 15 MSH2, and 1 MSH6). Twelve of these families (50%) are carriers of a novel mutation. Seven of the 15 positive MSH2 families (47%) are carriers of a rearrangement. The exon 7 deletion and exon 4 to 8 deletion of MSH2 are new founder mutations. The segregation of a common haplotype, a similar phenotype, and anticipation effects were observed in these families. These findings will greatly simplify the diagnosis, counseling, and clinical care in suspected Lynch syndrome families and not just in specific geographic areas, so wide distribution may be explained by migration patterns.