M. S. A. Bhuiyan

Genome-wide genetic diversity, population structure and admixture analysis in African and Asian cattle breeds

Knowledge about genetic diversity and population structure is useful for designing effective strategies to improve the production, management and conservation of farm animal genetic resources. Here, we present a comprehensive genome-wide analysis of genetic diversity, population structure and admixture based on 244 animals sampled from 10 cattle populations in Asia and Africa and genotyped for 69,903 autosomal single-nucleotide polymorphisms (SNPs) mainly derived from the indicine breed. Principal component analysis, STRUCTURE and distance analysis from high-density SNP data clearly revealed that the largest genetic difference occurred between the two domestic lineages (taurine and indicine), whereas Ethiopian cattle populations represent a mosaic of the humped zebu and taurine. Estimation of the genetic influence of zebu and taurine revealed that Ethiopian cattle were characterized by considerable levels of introgression from South Asian zebu, whereas Bangladeshi populations shared very low taurine ancestry. The relationships among Ethiopian cattle populations reflect their history of origin and admixture rather than phenotype-based distinctions. The high within-individual genetic variability observed in Ethiopian cattle represents an untapped opportunity for adaptation to changing environments and for implementation of within-breed genetic improvement schemes. Our results provide a basis for future applications of genome-wide SNP data to exploit the unique genetic makeup of indigenous cattle breeds and to facilitate their improvement and conservation.

Phenotypic Characterization of Aseel Chicken of Bangladesh

The aim of this study was to investigate phenotypic characteristics, morphometric measurements, reproduction and production performances of Aseel chicken of Bangladesh. The dominant feather color of neck/hackles was red in both males (56.14%) and females (54.16%) while the sickle feather color was mostly black in both chickens (71.93% vs. 54.17%). The predominant saddle and breast feather colors were red (40.35%) and black (64.91%), respectively, in male whereas most frequent observed color was pale brown in female (58.33 and 50.0%, respectively). The predominant feather color of wing bow and wing bay was found black (68.42 and 80.70%, respectively) in male but only pale brown color was observed in females (62.5 and 54.17%, respectively) for these two characters. Different phenotypic measurements such as the average shank length and circumference were 12.79 ± 0.13 and 7.8 ± 0.08 cm, respectively, in male and 10.21 ± 0.25 and 5.81 ± 0.21 cm, respectively, in female. Keel length was 14.39 ± 0.19 cm in male and 10.79 ± 0.23 cm in female. The average adult live weight in male was measured 3749.12 ± 83.44 g while in female it was 2062.50 ± 105.26 g. The age of 1st lay was found to be 28.86 weeks. Total number of eggs laid per year ranged between 24～48, number of clutch/hen/year varied from 2 to 4 and number of eggs/clutch/hen was found to be 10～12. The average live weight of Aseel chicken at 1, 2, 3, 4, 6, 8, 10, 12, 16 and 17 weeks of age were recorded as 31.14 ± 0.55, 48.63 ± 3.99, 116.57 ± 5.72, 138.40 ± 5.91, 212.88 ± 4.82, 361.00 ± 9.72, 577.50 ± 42.86, 743.75 ± 24.65, 1086.00 ± 26.02, 1402.00 ± 24.54 and 1432.00 ± 27.00 g respectively. Finally, this phenotypic characterization as well as productive and reproductive performances of Aseel chicken will give the baseline information to researcher for further study and for planning any on-ward conservation and implement strategy.

Genetic parameters of carcass and meat quality traits in different muscles (longissimus dorsi and semimembranosus) of Hanwoo (Korean cattle).

We estimated heritability () and genetic and phenotypic correlations for carcass and meat quality traits of longissimus dorsi (LD) and semimembranosus (SM) muscles in 30-mo-old Hanwoo steers. Variance and covariance components were estimated using REML procedures under univariate and bivariate models. The mean carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS) were 428.20 ± 46.30 kg, 87.38 ± 8.54 cm2, 13.00 ± 5.14 mm, and 5.21 ± 1.56, respectively. The mean CIE reflectance of meat lightness (L*), redness (a*), and yellowness (b*) were 40.01 ± 2.73, 22.37 ± 2.18, and 10.35 ± 1.46, respectively, in LD muscles and 36.33 ± 2.44, 22.91 ± 2.43, and 10.25 ± 1.65, respectively, in SM muscles. The mean Warner-Bratzler shear force (WBSF), intramuscular fat content (IMF), water-holding capacity (WHC), and protein and ash content in LD and SM muscles were 3.84 ± 0.96 and 6.52 ± 1.21 kg, 15.91 ± 4.39 and 5.10 ± 1.94%, 62.07 ± 3.38 and 71.61 ± 2.06%, 20.01 ± 1.39 and 21.34 ± 0.89%, and 0.80 ± 0.10 and 0.93 ± 0.07, respectively. The estimates of CWT, EMA, BFT, and MS were 0.51 ± 0.13, 0.45 ± 0.13, 0.29 ± 0.09, and 0.22 ± 0.08, respectively. The estimates were moderate for meat quality traits and were 0.37 ± 0.12, 0.40 ± 0.12, 0.33 ± 0.10, 0.33 ± 0.10, 0.30 ± 0.11, and 0.24 ± 0.09 for L*, WBSF, IMF, WHC, and protein and ash content, respectively, in LD muscle; estimates from SM muscle were comparatively low (0.08 ± 0.06 to 0.25 ± 0.09). Estimates of for a* and b* were also low (0.08 ± 0.06 to 0.13 ± 0.07). Carcass weight had a moderate, positive genetic correlation with EMA (0.60 ± 0.13) and a weak correlation with MS and BFT. The genetic correlations among the 3 colorimeter variants were strong and positive within and between muscles. Intramuscular fat content had moderate to strong and negative genetic correlations with WBSF (-0.49 ± 0.18), WHC (-0.99 ± 0.01), and protein (-0.93 ± 0.04) and ash content (-0.98 ± 0.06) in LD muscle, whereas the associations were less pronounced in SM muscle. In general, CWT and EMA had low genetic and phenotypic correlations with meat quality traits, which suggests that the traits are independent and have distinct genetic contributions in each muscle. Conversely, with few exceptions, meat quality traits had genetic and phenotypic correlations with MS and BFT. In conclusion, the estimated genetic parameters for carcass and meat quality traits could be used for genetic evaluation and breeding programs in Korean Hanwoo cattle populations.

Genetic Diversity and Phylogenetic Analysis of South-East Asian Duck Populations Based on the mtDNA D-loop Sequences

The maternally inherited mitochondrial DNA (mtDNA) D–loop region is widely used for exploring genetic relationships and for investigating the origin of various animal species. Currently, domestic ducks play an important role in animal protein supply. In this study, partial mtDNA D–loop sequences were obtained from 145 samples belonging to six South-East Asian duck populations and commercial duck population. All these populations were closely related to the mallard duck (Anas platyrhynchos), as indicated by their mean overall genetic distance. Sixteen nucleotide substitutions were identified in sequence analyses allowing the distinction of 28 haplotypes. Around 42.76% of the duck sequences were classified as Hap_02, which completely matched with Anas platyrhynchos duck species. The neighbor-joining phylogenetic tree also revealed that South-East Asian duck populations were closely related to Anas platyrhynchos. Network profiles were also traced using the 28 haplotypes. Overall, results showed that those duck populations D-loop haplotypes were shared between several duck breeds from Korea and Bangladesh sub continental regions. Therefore, these results confirmed that South-East Asian domestic duck populations have been domesticated from Anas platyrhynchos duck as the maternal origins.

Analysis of SNPs in Bovine CSRP3, APOBEC2 and Caveolin Gene Family

The cysteine and glycine rich protein 3 (CSRP3), apolipoprotein B mRNA editing enzyme catalytic polypeptide‐like 2(APOBEC2) and caveolin (CAV) gene family(CAV1, CAV2, CAV3) have been reported to play important roles for carcass and meat quality traits in pig, mouse, human and cattle. As an initial step, we investigated SNPs in these 5 genes among eight different cattle breeds. Eighteen primer pairs were designed from bovine sequence data of NCBI database to amplify the partial gene fragments. Sequencing results revealed 9 SNPs in the coding regions of three caveolin genes, 1 SNP in CSRP3 and 3 SNPs in APOBEC2 gene. All the identified SNPs were confirmed by PCR-RFLP. Also, 9 more intronic SNPs were detected in these genes. However, all identified mutations in the coding region do not change amino acid sequence. Allelic distributions were significantly different for 5 SNPs in CAV2, CAV3, CSRP3 and APOBEC2 genes among the eight different breeds. These results gave some clues about the polymorphisms of these genes among the cattle breeds and will be useful for further searches for identifying association between these SNPs and meat quality traits in cattle.

Genome-wide association study and prediction of genomic breeding values for fatty-acid composition in Korean Hanwoo cattle using a high-density single-nucleotide polymorphism array1

Genomic selection using high-density single-nucleotide polymorphism (SNP) markers is used in dairy and beef cattle breeds to accurately estimate genomic breeding values and accelerate genetic improvement by enabling selection of animals with high genetic merit. This genome-wide association study (GWAS) aimed to identify genetic variants associated with beef fatty-acid composition (FAC) traits and to evaluate the accuracy of genomic predictions (GPs) for those traits using genomic best linear unbiased prediction (GBLUP), pedigree BLUP (PBLUP), and BayesR models. Samples of the longissimus dorsi muscle of 965 thirty-month-old Hanwoo steers (progeny of 73 proven bulls) were used to investigate 14 FAC traits. Animals were genotyped or imputed using two bovine SNP platforms (50K and 777K), and after quality control, 38,715 (50K) and 633,448 (777K) SNPs were subjected to GWAS and GP study using a cross-validation scheme. SNP-based heritability estimates were moderate to high (0.25 to 0.47) for all studied traits, with some exceptions for polyunsaturated fatty acids. Association analysis revealed that 19 SNPs in BTA19 (98.7 kb) were significantly associated (P < 7.89 × 10-8) with C14:0 and C18:1n-9; these SNPs were in the fatty-acid synthase (FASN) and coiled-coil domain-containing 57 (CCDC57) genes. BayesR analysis revealed that 0.41 to 0.78% of the total SNPs (n = 2,571 to 4,904) explained almost all of the genetic variance; the majority of the SNPs (>99%) had negligible effects, suggesting that the FAC traits were polygenic. Genome partitioning analysis indicated mostly nonlinear and weak correlations between the variance explained by each chromosome and its length, which also reflected the considerable contributions of relatively few genes. The prediction accuracy of breeding values for FAC traits varied from low to high (0.25 to 0.57); the estimates using the GBLUP and BayesR methods were superior to those obtained by the PBLUP method. The BayesR method performed similarly to GBLUP for most of the studied traits but substantially better for those traits that were controlled by SNPs with large effects; this was supported by the GWAS results. In addition, the predictive abilities of the 50K and 777K SNP arrays were almost similar; thus, both are suitable for GP in Hanwoo cattle. In conclusion, this study provides important insight into the genetic architecture and predictive ability of FAC traits in Hanwoo cattle. Our findings could be used in selection and breeding programs to promote production of meat with enhanced nutritional value.

Functional Partitioning of Genomic Variance and Genome-Wide Association Study for Carcass Traits in Korean Hanwoo Cattle Using Imputed Sequence Level SNP Data

Quantitative traits are usually controlled by numerous genomic variants with small individual effects, and variances associated with those traits are explained in a continuous manner. However, the relative contributions of genomic regions to observed genetic variations have not been well explored using sequence level single nucleotide polymorphism (SNP) information. Here, imputed sequence level SNP data (11,278,153 SNPs) of 2109 Hanwoo steers (Korean native cattle) were partitioned according to functional annotation, chromosome, and minor allele frequency (MAF). Genomic relationship matrices (GRMs) were constructed for each classified region and fitted in the model both separately and together for carcass weight (CWT), eye muscle area (EMA), backfat thickness (BFT), and marbling score (MS) traits. A genome-wide association study (GWAS) was performed to identify significantly associated variants in genic and exon regions using a linear mixed model, and the genetic contribution of each exonic SNP was determined using a Bayesian mixture model. Considering all SNPs together, the heritability estimates for CWT, EMA, BFT, and MS were 0.57 ± 0.05, 0.46 ± 0.05, 0.45 ± 0.05, and 0.49 ± 0.05, respectively, which reflected substantial genomic contributions. Joint analysis revealed that the variance explained by each chromosome was proportional to its physical length with weak linear relationships for all traits. Moreover, genomic variances explained by functional category and MAF class differed greatly among the traits studied in joint analysis. For example, exon regions had larger contributions for BFT (0.13 ± 0.08) and MS (0.22 ± 0.08), whereas intron and intergenic regions explained most of the total genomic variances for CWT and EMA (0.22 ± 0.09–0.32 ± 0.11). Considering different functional classes of exon regions and the per SNP contribution revealed the largest proportion of genetic variance was attributable to synonymous variants. GWAS detected 206 and 27 SNPs in genic and exon regions, respectively, on BTA4, BTA6, and BTA14 that were significantly associated with CWT and EMA. These SNPs were harbored by 31 candidate genes, among which TOX, FAM184B, PPARGC1A, PRKDC, LCORL, and COL1A2 were noteworthy. BayesR analysis found that most SNPs (>93%) had very small effects and the 4.02–6.92% that had larger effects (10-4 × σA2, 10-3 × σA2, and 10-2 × σA2) explained most of the total genetic variance, confirming polygenic components of the traits studied.