Genetic parameters of body weight traits in Mithun (Bos frontalis) using animal model.

Mithun (Bos frontalis), a domestically raised herbivore, holds significant economic importance for the farming community of Northeast India. This study aimed to elucidate the genetic parameters governing Mithun body weight traits across different ages using data from the sole organized semi-intensive Mithun farm in India. Information was gathered from 110 Mithuns born over a period spanning from 2011 to 2022. Body weight taken at week 1 (W1), 1-month (M1), 3-months (M3), 6-months (M6), 9-months (M9), 12-months (M12), 30-months (M30) and 45-months (M45) were considered for the study. The genetic parameters estimation employed the BLUPF90 suite of programs, incorporating univariate Gibbs sampler animal model with fixed effects; season and period of birth, and sex of the animal. Variance and covariance components, including direct additive genetic effects, were estimated. Heritability estimates for the eight body weight traits ranged from 0.47 ± 0.0050 to 0.50 ± 0.0043, indicating varying genetic influence across growth stages. Results revealed that Mithun herd has a substantial genetic variability for growth traits and therefore there is ample scope to select for a better growth rate. Here, we conclude that Month 12 (M12) and Month 9 (M9) body weights exhibit higher heritability, indicating potential for genetic improvement through selective breeding.

Phenomics in Livestock Research: Bottlenecks and Promises of Digital Phenotyping and Other Quantification Techniques on a Global Scale.

Bottlenecks in moving genomics to real-life applications also include phenomics. This is true not only for genomics medicine and public health genomics but also in ecology and livestock phenomics. This expert narrative review explores the intricate relationship between genetic makeup and observable phenotypic traits across various biological levels in the context of livestock research. We unpack and emphasize the significance of precise phenotypic data in selective breeding outcomes and examine the multifaceted applications of phenomics, ranging from improvement to assessing welfare, reproductive traits, and environmental adaptation in livestock. As phenotypic traits exhibit strong correlations, their measurement alongside specific biological outcomes provides insights into performance, overall health, and clinical endpoints like morbidity and disease. In addition, automated assessment of livestock holds potential for monitoring the dynamic phenotypic traits across various species, facilitating a deeper comprehension of how they adapt to their environment and attendant stressors. A key challenge in genetic improvement in livestock is predicting individuals with optimal fitness without direct measurement. Temporal predictions from unmanned aerial systems can surpass genomic predictions, offering in-depth data on livestock. In the near future, digital phenotyping and digital biomarkers may further unravel the genetic intricacies of stress tolerance, adaptation and welfare aspects of animals enabling the selection of climate-resilient and productive livestock. This expert review thus delves into challenges associated with phenotyping and discusses technological advancements shaping the future of biological research concerning livestock.

Studies on pollen micro-morphology, pollen storage methods, and cross-compatibility among grape (Vitis spp.) genotypes.

The knowledge of pollen morphology, suitable storage condition, and species compatibility is vital for a successful grapevine improvement programme. Ten grape genotypes from three different species, viz., Vitis vinifera L., Vitis parviflora Roxb., and Vitis champini Planc., were studied for their pollen structure and pollen storage with the objective of determining their utilization in grape rootstock improvement programs. Pollen morphology was examined through the use of a scanning electron microscope (SEM). The viability of the pollen was assessed using 2,3,5-triphenyltetrazolium chloride (TTC). In vitro pollen germination was investigated using the semi-solid medium with 10 % sucrose, 100 mg/L boric acid, and 300 mg/L calcium nitrate. The results revealed variations in pollen micro-morphology in 10 genotypes, with distinct pollen dimensions, shapes, and exine ornamentation. However, species-wise, no clear difference was found for these parameters. Pollen of V. parviflora Roxb. and Dogridge was acolporated and did not germinate. The remaining eight genotypes exhibited tricolporated pollen and showed satisfactory in vitro pollen germination. Storage temperature and duration interactions showed that, at room temperature, pollen of most of the grape genotypes can be stored for up to 1 day only with an acceptable pollen germination rate (>30 %). However, storage for up to 7 days was successfully achieved at 4 °C, except for 'Pearl of Csaba'. The most effective storage conditions were found to be at -20 °C and -196 °C (in liquid N2), enabling pollen storage for a period of up to 30 days, and can be used for pollination to overcome the challenge of asynchronous flowering. Four interspecific combinations were studied for their compatibility, among which V. parviflora Roxb. × V. vinifera L. (Pusa Navrang) and V. parviflora Roxb. × V. champini Planc. (Salt Creek) showed high cross-compatibility, offering their potential use for grape rootstock breeding. However, V. parviflora Roxb. × V. vinifera L. (Male Hybrid) recorded the lowest compatibility index among studied crosses. In the case of self-pollinated flowers from V. parviflora Roxb. and V. parviflora Roxb. × V. champini Planc. (Dogridge), pollen failed to germinate on the stigma due to male sterility caused by acolporated pollen. As a result, the flowers of these genotypes functioned as females, which means they are ideal female parents for grape breeding without the need for the tedious process of emasculation.

Bottom-up approach to explore alpha-amylase assisted membrane remodelling.

Soluble alpha-amylases play an important role in the catabolism of polysaccharides. In this work, we show that the malt α -amylase can interact with the lipid membrane and further alter its mechanical properties. Vesicle fluctuation spectroscopy is used for quantitative measurement of the membrane bending rigidity of phosphatidylcholines lipid vesicles from the shape fluctuation based on the whole contour of Giant Unilamellar Vesicles (GUVs). The bending rigidity of the 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine lipid vesicles in water increases significantly with the presence of 0.14 micromolar alpha-amylase (AA) in the exterior solution. It appears that the enzyme present in the external solution interacts with the outer layer of the bilayer membrane, leading to an asymmetry of the solution on either side of the bilayer membrane and altering its elasticity. At AA concentration of 1.5 micromolars and above, changes in the morphology of the GUV membrane are observed. The interaction between AA in the external solution and the external leaflet causes the bilayer membrane to curve spontaneously, leading to the formation of outbuds, giving a positive spontaneous curvature of C0 ≤ 0.05 µm-1 at ≈ 1 mg / ml of the AA concentration. We validate and characterize its concentration-dependent role in stabilizing the membrane curvature. Our findings indicate that the involvement of the enzyme, depending on the concentration, can have a considerable effect on the mechanical characteristics of the membrane.

First report of Ikeda genotype of Theileria orientalis in Mithun (Bos frontalis) from northeastern hilly region of India.

Oriental theileriosis caused by Theileria orientalis, previously considered a benign disease, is posing a significant threat to the livestock industry across the globe. To elucidate the prevalence of Theileria orientalis in ticks and their host, the Mithun, a comprehensive study was undertaken in the two northeastern states of India, viz. Nagaland and Arunachal Pradesh. A total of 340 of Rhipicephalus microplus ticks and 25 Ambylomma sp. ticks were screened for the presence of Theileria orientalis through PCR. Among the R. microplus ticks examined, 25 of them tested positive for T. orientalis infection whereas none of the Amblyomma ticks was positive. Additionally, a total of 275 blood samples were collected from Mithun from Arunachal and Nagaland and 31 animals were found to be positive for T. orientalis infection. Notably, six positive cases were identified in Porba (Phek district), six in Tening, and one in Bamsiakilwa village (Peren district) of Nagaland. Moreover, out of the 41 animals examined at Medziphema farms, Nagaland, 18 were found to be positive for T. orientalis infection. Moreover, the phylogenetic investigation has unveiled the presence of the highly pathogenic Type 2 (Ikeda) T. orientalis genotype in Mithun, supported by a strong bootstrap value of 100%. This study marks the initial documentation of oriental theileriosis in mithun. It underscores the need for vigilant monitoring and active surveillance of mithun populations in the northeastern states of India. Timely treatment of infected animals is imperative to avert economic losses for the farmers.

Uncovering genes underlying coat color variation in indigenous cattle breeds through genome-wide positive selection.

The identification of candidate genes related to pigmentation and under selective sweep provides insights into the genetic basis of pigmentation and the evolutionary forces that have shaped this variation. The selective sweep events in the genes responsible for normal coat color in Indian cattle groups are still unknown. To find coat color genes displaying signs of selective sweeps in the indigenous cattle, we compiled a list of candidate genes previously investigated for their association with coat color and pigmentation. After that, we performed a genome-wide scan of positive selection signatures using the BovineSNP50K Bead Chip in 187 individuals of seven indigenous breeds. We applied a wide range of methods to find evidence of selection, such as Tajima's D, CLR, iHS, varLD, ROH, and FST. We found a total of sixteen genes under selective sweep, that were involved in coat color and pigmentation physiology. These genes are CRIM1 in Gir, MC1R in Sahiwal, MYO5A, PMEL and POMC in Tharparkar, TYRP1, ERBB2, and ASIP in Red Sindhi, MITF, LOC789175, PAX3 and TYR in Ongole, and IRF2, SDR165 and, KIT in Nelore, ADAMTS19 in Hariana. These genes are related to melanin synthesis, the biology of melanocytes and melanosomes, and the migration and survival of melanocytes during development.

Detection of genome-wide copy number variation in Murrah buffaloes.

Riverine Buffaloes, especially the Murrah breed because of their adaptability to harsh climatic conditions, is farmed in many countries to convert low-quality feed into valuable dairy products and meat. Here, we investigated the copy number variations (CNVs) in 296 Murrah buffalo using the Axiom® Buffalo Genotyping Array 90K (Affymetrix, Santa Clara, CA, USA). The CNVs were detected on the autosomes, using the Copy Number Analysis Module (CNAM) using the univariate analysis. 7937 CNVs were detected in 279 Buffaloes, the average length of the CNVs was 119,048.87 bp that ranged between 7800 and 4,561,030 bp. These CNVs were accounting for 10.33% of the buffalo genome, which was comparable to cattle, sheep, and goat CNV analyses. Further, CNVs were merged and 1541 CNVRs were detected using the Bedtools-mergeBed command. 485 genes were annotated within 196 CNVRs that were identified in at least 10 animals of Murrah population. Out of these, 40 CNVRs contained 59 different genes that were associated with 69 different traits. Overall, the study identified a significant number of CNVs and CNVRs in the Murrah breed of buffalo, with a wide range of lengths and frequencies across the autosomes. The identified CNVRs contained genes associated with important traits related to production and reproduction, making them potentially important targets for future breeding and genetic improvement efforts.

Evidence for selective sweeps in the MHC gene repertoire of various cattle breeds.

Major Histocompatibility Complex (MHC) genes are among the immune genes that have been extensively studied in vertebrates and are necessary for adaptive immunity. In the immunological response to infectious diseases, they play several significant roles. This research paper provides the selection signatures in the MHC region of the bovine genome as well as how certain genes related to innate immunity are undergoing a positive selective sweep. Here, we investigated signatures of historical selection on MHC genes in 15 different cattle populations and a total of 427 individuals. To identify the selection signatures, we have used three separate summary statistics. The findings show potential selection signatures in cattle from whom we isolated genes involved in the MHC. The most significant regions related to the bovine MHC are BOLA, non-classical MHC class I antigen (BOLA-NC1), Microneme protein 1 (MIC1) , Cluster of Differentiation 244 (CD244), Gap Junction Alpha-5 Protein (GJA5). It will be possible to gain new insight into immune system evolution by understanding the distinctive characteristics of MHC in cattle.

Progress and future perspectives of livestock genomics in India: a mini review.

The field of genetics has evolved a lot after the emergence of molecular and advanced genomic technologies. The advent of Next Generation Sequencing, SNP genotyping platforms and simultaneous reduction in the cost of sequencing had opened the door to genomic research in farm animals. There are various applications of genomics in livestock, such as the use of genomic data: (i) to investigate genetic diversity and breed composition/population structure (ii) to identify genetic variants and QTLs related to economically important and ecological traits, genome-wide association studies (GWAS) and genomic signatures of selection; (iii) to enhance breeding programs by genomic selection. Compared to traditional methods, genomic selection is expected to improve selection response by increasing selection accuracy and reducing the generation interval due to early selection. Genomic selection (GS) in developed countries has led to rapid genetic gains, especially in dairy cattle, due to a well-established genetic evaluation system. Indian livestock system is still lagging behind developed nations in adopting these technologies. This review discusses the current status, challenges, and future perspectives of livestock genomics in India.

Selection signatures for fiber production in commercial species: A review.

Natural fibers derived from diverse animal species have gained increased attention in recent years due to their favorable environmental effects, long-term sustainability benefits, and remarkable physical and mechanical properties that make them valuable raw materials used for textile and non-textile production. Domestication and selective breeding for the economically significant fiber traits play an imperative role in shaping the genomes and, thus, positively impact the overall productivity of the various fiber-producing species. These selection pressures leave unique footprints on the genome due to alteration in the allelic frequencies at specific loci, characterizing selective sweeps. Recent advances in genomics have enabled the discovery of selection signatures across the genome using a variety of methods. The increased demand for 'green products' manufactured from natural fibers necessitates a detailed investigation of the genomes of the various fiber-producing plant and animal species to identify the candidate genes associated with important fiber attributes such as fiber diameter/fineness, color, length, and strength, among others. The objective of this review is to present a comprehensive overview of the concept of selection signature and selective sweeps, discuss the main methods used for its detection, and address the selection signature studies conducted so far in the diverse fiber-producing animal species.

Molecular and phylogenetic analysis of MHC class I exons 7-8 in a variety of cattle and buffalo breeds.

The present study was conducted on the MHC class I (BoLA-A/BuLA-A) gene in Sahiwal, Jersey, Hariana, and Tharparkar breeds of cattle and Murrah, Mehsana, and Bhadawari breeds of buffalo to study the polymorphism. Exons 7-8 of the MHC class I gene was first characterized for polymorphism study in buffalo and the results reveal that this gene has a higher level of nucleotide changes than the cattle. Genes were investigated for polymorphisms in 285 animals of cattle and buffalo breeds. Molecular characterization of the MHC class I (BoLa-A/Bula-A) gene reveals a higher degree of polymorphism at the nucleotide level in cattle and buffalo. Results revealed this region has a higher level of polymorphisms in buffalo as campared to the cattle. Alul restriction patterns were monomorphic except for three different patterns but it was able to illustrate the differences in buffalo and cattle. SSCP analysis of exons 7-8 showed remarkable differences in cattle and buffalo. Sequence analysis revealed more closeness of Murrah breed with crossbred and indigenous cattle than Holstein Friesian. Exon 8 had more deletion and stop codon as compared to exon 7. The investigation confirmed that MHC class I BoLa-A/Bula-A exons 7-8 is highly polymorphic in buffalo as compared to cattle.

Characterization of BoLA class II DQA and DQB by PCR-RFLP, cloning, and sequencing reveals sequence diversity in crossbred cattle.

The BoLA class II DQA and DQB genes in crossbred cattle were studied using PCR-RFLP, cloning, and sequencing techniques. Seventy-two crossbred cattle (Vrindavani) were used in the current study. HaeIII and XbaI restriction enzymes digested DQA exon 2-3, revealing seven (HaeIII-A-G) and three (XbaI A-C) motifs, respectively. The BoLA-DQB gene was analyzed using PCR-RFLP with PstI and TaqI restriction enzymes, yielding five restriction motifs for each restriction enzyme (PstI-A-E and TaqI-A-E). In crossbred cattle, addition, deletion, and substitutions were observed in distinct sequences, resulting in variations in overall gene length. Changes in nucleotides at positions 64-80, 110-200, and 207-264 were largely responsible for polymorphism in DQA exon 2. The phylogenetic analysis predicted a high degree of nucleotide and amino acid changes in DQA exon 2-3 and DQB exon 2. DQA genes had a nucleotide dissimilarity of 0.3-25.4 percent, while DQB genes had a nucleotide dissimilarity of 1.5-14.3 percent. We cloned and sequenced 20 genotypes based on PCR-RFLP of the DQA and DQB genes. The current study observed variation in the DQA and DQB genes and will serve as a foundation for future research on the BoLA DQA and DQB genes.

Genome-wide detection of copy number variations in Tharparkar cattle.

Copy number variations (CNVs) are major forms of genetic variation with an increasing importance in animal genomics. This study used the Illumina BovineSNP 50 K BeadChip to detect the genome-wide CNVs in the Tharparkar cattle. With the aid of PennCNV software, we noticed a total of 447 copy number variation regions (CNVRs) across the autosomal genome, occupying nearly 2.17% of the bovine genome. The average size of detected CNVRs was found to be 122.2 kb, the smallest CNVR being 50.02 kb in size, to the largest being 1,232.87 Kb. Enrichment analyses of the genes in these CNVRs gave significant associations with molecular adaptation-related Gene Ontology (GO) terms. Most CNVR genes were significantly enriched for specific biological functions; signaling pathways, sensory responses to stimuli, and various cellular processes. In addition, QTL analysis of CNVRs described them to be linked with economically essential traits in cattle. The findings here provide crucial information for constructing a more comprehensive CNVR map for the indigenous cattle genome.

Signatures of selection in riverine buffalo populations revealed by genome-wide SNP data.

The detection of selection signatures assists in understanding domestication, evolution, and the identification of genomic regions related to adaptation and production traits in buffaloes. The emergence of high-throughput technologies like Next Generation Sequencing and SNP genotyping had expanded our ability to detect these signatures of selection. In this study, we sought to identify signatures of selection in five buffalo populations (Brazilian Murrah, Bulgarian Murrah, Indian Murrah, Nili-Ravi, and Kundi) using Axiom Buffalo 90 K Genotyping Array data. Using seven different methodologies (Tajima's D, CLR, ROH, iHS, FST, FLK and hapFLK), we identified selection signatures in 374 genomic regions, spanning a total of 381 genes and 350 quantitative trait loci (QTLs). Among these, several candidate genes were associated with QTLs for milk production, reproduction, growth and carcass traits. The genes and QTLs reported in this study provide insight into selection signals shaping the genome of buffalo breeds. Our findings can aid in further genomic association studies, genomic prediction, and the implementation of breeding programmes in Indian buffaloes.

Trajectory of livestock genomics in South Asia: A comprehensive review.

Livestock plays a central role in sustaining human livelihood in South Asia. There are numerous and distinct livestock species in South Asian countries. Several of them have experienced genetic development in recent years due to the application of genomic technologies and effective breeding programs. This review discusses genomic studies on cattle, buffalo, sheep, goat, pig, horse, camel, yak, mithun, and poultry. The frontiers covered in this review are genetic diversity, admixture studies, selection signature research, QTL discovery, genome-wide association studies (GWAS), and genomic selection. The review concludes with recommendations for South Asian livestock systems to increasingly leverage genomic technologies, based on the lessons learned from the numerous case studies. This paper aims to present a comprehensive analysis of the dichotomy in the South Asian livestock sector and argues that a realistic approach to genomics in livestock can ensure long-term genetic advancements.

'Comparison and correlation of the maxillary sinus dimensions in various craniofacial patterns: A CBCT Study'.

Background: To compare and correlate the maxillary sinus dimensions and basal bone height among various facial patterns using CBCT for advanced diagnosis and treatment planning in Orthodontics. Methods: 66 CBCT images within age group of 18-30 years were divided into horizontal (Group 1), average (Group 2) and vertical (Group 3) facial growth patterns. Maxillary sinus dimensions were compared and correlated in all three groups. The sinus height and basal bone height were recorded at 3 locations-between 1 st premolar and 2 nd premolar (PM1-PM2), between 2 nd premolar and 1 st Molar (PM2-M1) and between 1 st and 2 nd molar (M1-M2). Results: Overall reduction in sinus height and significantly reduced sinus volume was seen in Group-1. Longest maxillary sinus height in M1-M2 region and shortest in PM1-PM2 region was seen in Group-3. The basal bone height in PM1-PM2 region was significantly longer in Group-3 than in Group-1(p<.05).Shortest basal bone height in M1-M2 region was seen in Group-3. A significant negative correlation was seen between the maxillary sinus height and the basal bone height in Group-1 and Group-3(p<.05). Conclusion: There is a correlation between the maxillary sinus height and basal bone height with that of facial pattern which needs to be considered during orthodontic treatment planning and while carrying out facial growth modification procedures in younger patients.

Machine-Learning Prospects for Detecting Selection Signatures Using Population Genomics Data.

Natural selection has been given a lot of attention because it relates to the adaptation of populations to their environments, both biotic and abiotic. An allele is selected when it is favored by natural selection. Consequently, the favored allele increases in frequency in the population and neighboring linked variation diminishes, causing so-called selective sweeps. A high-throughput genomic sequence allows one to disentangle the evolutionary forces at play in populations. With the development of high-throughput genome sequencing technologies, it has become easier to detect these selective sweeps/selection signatures. Various methods can be used to detect selective sweeps, from simple implementations using summary statistics to complex statistical approaches. One of the important problems of these statistical models is the potential to provide inaccurate results when their assumptions are violated. The use of machine learning (ML) in population genetics has been introduced as an alternative method of detecting selection by treating the problem of detecting selection signatures as a classification problem. Since the availability of population genomics data is increasing, researchers may incorporate ML into these statistical models to infer signatures of selection with higher predictive accuracy and better resolution. This article describes how ML can be used to aid in detecting and studying natural selection patterns using population genomic data.

Molecular characterization of CRBR2 fragment of TLR4 gene in association with mastitis in Vrindavani cattle.

The bovine TLR4 gene is an interesting candidate marker for mastitis resistance, since it is involved in neutrophil migration to and from the mammary gland during mastitis. TLR4 detects pathogen ligands, such as the Escherichia coli lipopolysaccharide (LPS) endotoxin and facilitates innate and adaptive immune responses. In the current study, a total of 130 crossbred cows (74 mastitis tolerant and 56 with clinical mastitis) kept at the Cattle and Buffalo Farm, IVRI, Izatnagar, were selected to explore the polymorphism in the co-receptor binding region 2 (CRBR2) fragment of the TLR4 gene. PCR-SSCP and sequence analysis showed two genotypes of the TLR4 gene's CRBR2 fragment, AA and AB, which were polymorphic in both the afflicted and tolerant groups. Sequencing revealed eight single nucleotide polymorphisms (SNPs) in allele A and ten SNPs in allele B. This genotype had no significant effect on the incidence of clinical mastitis according to the logistic regression model. Our study found insufficient evidence linking SNP variants in the CRBR2 region of the TLR4 gene to mastitis susceptibility in crossbred cattle.

Unraveling genetic admixture in the Indian crossbred cattle by different approaches using Bovine 50K BeadChip.

With the upsurge of crossbreeding in India, the admixture levels are highly unpredictable in the composite breeds. Hence, in the present study, 72 Vrindavani animals were assessed for the level of admixture from their known ancestors that are Holstein-Friesian, Jersey, Brown Swiss, and Hariana, through three different software, namely, STRUCTURE, ADMIXTURE, and frappe. The genotype data for ancestral breeds were obtained from a public repository, i.e., DRYAD. The Frieswal crossbred cattle along with ancestral breeds like Holstein-Friesian and Sahiwal were also investigated for the level of admixture with the help of the above-mentioned software. The Frieswal population was found to comprise an average of 62.49, 61.12, and 61.21% of Holstein-Friesian and 37.50, 38.88, and 38.80% of Sahiwal estimated through STRUCTURE, ADMIXTURE, and frappe, respectively. The Vrindavani population was found to consist of on average 39.5, 42.4, and 42.3% of Holstein-Friesian; 22.9, 22.3, and 21.7% of Jersey; 10.7, 10.6, and 11.9% of Brown Swiss; and 26.9, 24.7, and 24.1% of Hariana blood estimated through STRUCTURE, ADMIXTURE, and frappe, respectively. A greater degree of variation was noted in the results from STRUCTURE vs. frappe, STRUCTURE vs. ADMIXTURE than in ADMIXTURE vs. frappe. From this study, we conclude that the admixture analysis based on a single software should be validated through the use of many different approaches for better prediction of admixture levels.

Role of genomics in combating COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) quickly swept over the world, becoming one of the most devastating outbreaks in human history. Being the first pandemic in the post-genomic era, advancements in genomics contributed significantly to scientific understanding and public health response to COVID-19. Genomic technologies have been employed by researchers all over the world to better understand the biology of SARS-CoV-2 and its origin, genomic diversity, and evolution. Worldwide genomic resources have greatly aided in the investigation of the COVID-19 pandemic. The pandemic has ushered in a new era of genomic surveillance, wherein scientists are tracking the changes of the SARS-CoV-2 genome in real-time at the international and national levels. Availability of genomic and proteomic information enables the rapid development of molecular diagnostics and therapeutics. The advent of high-throughput sequencing and genome editing technologies led to the development of modern vaccines. We briefly discuss the impact of genomics in the ongoing COVID-19 pandemic in this review.