2 research outputs found
Risk of sperm disorders and impaired fertility in frozenβthawed bull semen: a genome-wide association study
Simple Summary
This study tackles the genetic aspects of the risk of sperm damage and related impaired fertility when handling frozenβthawed bull semen for artificial insemination. To this end, we performed genomic association analysis to identify relevant genetic markers and candidate genes associated with various abnormalities in frozenβthawed Holstein cattle sperm. The results provide important insights into the molecular mechanisms underlying sperm morphology and abnormalities after cryopreservation. Further research is needed to explore causative genetic variants and implement these findings to improve animal reproduction and breeding.
Abstract
Cryopreservation is a widely used method of semen conservation in animal breeding programs. This process, however, can have a detrimental effect on sperm quality, especially in terms of its morphology. The resultant sperm disorders raise the risk of reduced sperm fertilizing ability, which poses a serious threat to the long-term efficacy of livestock reproduction and breeding. Understanding the genetic factors underlying these effects is critical for maintaining sperm quality during cryopreservation, and for animal fertility in general. In this regard, we performed a genome-wide association study to identify genomic regions associated with various cryopreservation sperm abnormalities in Holstein cattle, using single nucleotide polymorphism (SNP) markers via a high-density genotyping assay. Our analysis revealed a significant association of specific SNPs and candidate genes with absence of acrosomes, damaged cell necks and tails, as well as wrinkled acrosomes and decreased motility of cryopreserved sperm. As a result, we identified candidate genes such as POU6F2, LPCAT4, DPYD, SLC39A12 and CACNB2, as well as microRNAs (bta-mir-137 and bta-mir-2420) that may play a critical role in sperm morphology and disorders. These findings provide crucial information on the molecular mechanisms underlying acrosome integrity, motility, head abnormalities and damaged cell necks and tails of sperm after cryopreservation. Further studies with larger sample sizes, genome-wide coverage and functional validation are needed to explore causal variants in more detail, thereby elucidating the mechanisms mediating these effects. Overall, our results contribute to the understanding of genetic architecture in cryopreserved semen quality and disorders in bulls, laying the foundation for improved animal reproduction and breeding
[Studying the structure of a gene pool population of the Russian White chicken breed by genome-wide SNP scan] ΠΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΡΡΡΡΠΊΡΡΡΡ Π³Π΅Π½ΠΎΡΠΎΠ½Π΄Π½ΠΎΠΉ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ ΡΡΡΡΠΊΠΎΠΉ Π±Π΅Π»ΠΎΠΉ ΠΏΠΎΡΠΎΠ΄Ρ ΠΊΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π³Π΅Π½ΠΎΠΌΠ½ΠΎΠ³ΠΎ SNP-ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ
A population of the Russian White chickens, bred at the gene pool farm of ARRIFAGB for 25 generations using individual selection, is characterized by resistance to a lowered temperature in the early postnatal period and white colour of the embryonic down. In 2002-2012, breeding was carried out by panmixia, and by now a new population of the Russian White chickens has been formed on the basis of the surviving stock. Comparison of the genetic variability of this population and the archival DNA of representatives of the 2001 population using microarray screening technology will help to assess the population structure and the preservation of the unique characteristics of its genome. The material for the study was DNA extracted from 162 chicken blood samples. Two groups of the Russian White breed were studied, the 2001 population and the current population. Genome-wide analysis using single nucleotide markers (SNP) included screening by means of the Illumina Chicken 60K SNP iSelect BeadChip microarray. Quality control of genotyping, determination of the population genetic structure by multidimensional scaling (MDS), calculation of linkage disequilibrium (LD) and allele frequency in the groups were carried out using PLINK 1.9 software program. The construction of a cluster delimitation model based on SNP genotypes was carried out using the ADMIXTURE program. According to the MDS analysis results, the current population can be divided into four MDS groups, which, when compared to the data of the pedigree, adequately reflect the origin of the studied individuals. The representatives of the ancestral population were genetically similar to the MDS3 group of the current population. Using the F-statistic of the two-way analysis of variance, a significant effect of the group, chromosome, chromosome in the group, and the distance between SNP markers on LD (r2) values was observed. In the 2001 group, the maximum r2 and the high incidence of LD equal to 1 were observed for all chromosomes, with a distance between SNP markers being 500-1000 Kb. There was also the greatest number of monomorphic alleles in this group. Based on the SNP analysis, we may conclude that the current Russian White chicken population is characterized by the disintegration of long LD regions of the ancestral population. Modelling clusters using the ADMIXTURE program revealed differences between the current population groups determined by MDS analysis. The groups composed of individuals included in MDS1 and MDS2 had a homogeneous structure and differed from each other at K = 4 and K = 5. The MDS4 group formed a genetically heterogeneous cluster different from the MDS1 and MDS2 groups at K of 2-5. The MDS3 group was phylogenetically close to the 2001 population (at K of 2-5). In general, the analysis of the current gene pool population of the Russian White chickens showed its heterogeneity while one of its groups (MDS3) was similar to the ancestral population of 2001, which in turn is characterized by a large number of monomorphic alleles and a high frequency of long LD regions. Thus, SNP scanning allowed evaluating the genetic similarity of individuals and the population structure of the Russian White chicken breed. Understanding the genetic structure is an important point in the panmictic breeding and tracking of historical changes in the molecular organization of the genome of a gene pool population with a limited number of animals.
ΠΠΎΠΏΡΠ»ΡΡΠΈΡ ΡΡΡΡΠΊΠΈΡ
Π±Π΅Π»ΡΡ
ΠΊΡΡ ΡΠ΅Π»Π΅ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π»Π°ΡΡ Π² Π³Π΅Π½ΠΎΡΠΎΠ½Π΄Π½ΠΎΠΌ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅ ΠΡΠ΅ΡΠΎΡΡΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΠΠΠ Π³Π΅Π½Π΅ΡΠΈΠΊΠΈ ΠΈ ΡΠ°Π·Π²Π΅Π΄Π΅Π½ΠΈΡ ΡΠ΅Π»ΡΡΠΊΠΎΡ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΡΡ
ΠΆΠΈΠ²ΠΎΡΠ½ΡΡ
(ΠΠΠΠΠΠ Π) Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ 25 ΠΏΠΎΠΊΠΎΠ»Π΅Π½ΠΈΠΉ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Π±ΠΎΡΠ°. ΠΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΡΡΠΎΠΉ ΠΏΠΎΡΠΎΠ΄Ρ β ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΡ ΠΊ ΠΏΠΎΠ½ΠΈΠΆΠ΅Π½Π½ΠΎΠΉ ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΠ΅ Π²ΡΡΠ°ΡΠΈΠ²Π°Π½ΠΈΡ Π² ΡΠ°Π½Π½ΠΈΠΉ ΠΏΠΎΡΡΠ½Π°ΡΠ°Π»ΡΠ½ΡΠΉ ΠΏΠ΅ΡΠΈΠΎΠ΄ ΠΈ Π±Π΅Π»ΡΠΉ ΡΠ²Π΅Ρ ΡΠΌΠ±ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΡΡ
Π°. Π 2002-2012 Π³ΠΎΠ΄Π°Ρ
Π΅Π΅ ΡΠ°Π·Π²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ»ΠΎΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΏΠ°Π½ΠΌΠΈΠΊΡΠΈΠΈ, ΠΈ ΠΊ Π½Π°ΡΡΠΎΡΡΠ΅ΠΌΡ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠΎΡ
ΡΠ°Π½ΠΈΠ²ΡΠ΅Π³ΠΎΡΡ ΠΏΠΎΠ³ΠΎΠ»ΠΎΠ²ΡΡ ΡΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½Π° Π½ΠΎΠ²Π°Ρ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΡ ΡΡΡΡΠΊΠΈΡ
Π±Π΅Π»ΡΡ
ΠΊΡΡ. ΠΠ°ΡΠ΅ΠΉ ΡΠ΅Π»ΡΡ Π±ΡΠ»ΠΎ ΠΏΠΎΠΊΠ°Π·Π°ΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΏΠΎΠ»Π½ΠΎΠ³Π΅Π½ΠΎΠΌΠ½ΠΎΠ³ΠΎ SNP-ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ (single nucleotide polymorphisms) Π΄Π»Ρ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ Π³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΡΡΡΡΠΊΡΡΡΡ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ ΠΌΠ°Π»ΠΎΡΠΈΡΠ»Π΅Π½Π½ΡΡ
ΠΏΠΎΡΠΎΠ΄ ΠΊΡΡ ΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΠΈΡΡ
ΠΎΠΆΠ΄Π΅Π½ΠΈΡ ΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΌΠΎΠ»Π΅ΠΊΡΠ»ΡΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ Π½Π° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ ΡΡΡΡΠΊΠΎΠΉ Π±Π΅Π»ΠΎΠΉ ΠΏΠΎΡΠΎΠ΄Ρ Ρ ΠΏΡΠ΅Π΄ΠΊΠΎΠ²ΠΎΠΉ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠ΅ΠΉ 2001 Π³ΠΎΠ΄Π°. ΠΡΠ»ΠΈ ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ Π΄Π²Π΅ Π³ΡΡΠΏΠΏΡ ΠΊΡΡ: ΠΏΠΎΠΏΡΠ»ΡΡΠΈΡ 2001 Π³ΠΎΠ΄Π° (6 Π³ΠΎΠ»., Π½Π΅ΡΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΠ΅ ΠΎΡΠΎΠ±ΠΈ ΠΈΠ· Π΄Π²ΡΡ
Π»ΠΈΠ½ΠΈΠΉ) ΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½Π°Ρ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΡ (156 Π³ΠΎΠ».). SNP-Π°Π½Π°Π»ΠΈΠ· Π²ΠΊΠ»ΡΡΠ°Π» ΡΠΊΡΠΈΠ½ΠΈΠ½Π³ 162 ΠΎΠ±ΡΠ°Π·ΡΠΎΠ² ΠΠΠ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΠΌΠΈΠΊΡΠΎΡΠΈΠΏΠ° Illumina Chicken 60K SNP iSelect BeadChip (Β«IlluminaΒ», Π‘Π¨Π). ΠΠΎΠ½ΡΡΠΎΠ»Ρ ΠΊΠ°ΡΠ΅ΡΡΠ²Π° Π³Π΅Π½ΠΎΡΠΈΠΏΠΈΡΠΎΠ²Π°Π½ΠΈΡ, ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Π³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΡΡΡΠΊΡΡΡΡ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΌΠ½ΠΎΠ³ΠΎΠΌΠ΅ΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠ°Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ (multidimensional scaling, MDS), ΡΠ°ΡΡΠ΅Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Π½Π΅ΡΠ°Π²Π½ΠΎΠ²Π΅ΡΠ½ΠΎΠ³ΠΎ ΡΡΠ΅ΠΏΠ»Π΅Π½ΠΈΡ (linkage disequilibrium, LD) ΠΈ ΡΠ°ΡΡΠΎΡΡ Π²ΡΡΡΠ΅ΡΠ°Π΅ΠΌΠΎΡΡΠΈ Π°Π»Π»Π΅Π΅ΠΉ ΠΏΠΎ Π³ΡΡΠΏΠΏΠ°ΠΌ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Π² ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ΅ PLINK 1.9. ΠΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠ°Π·Π³ΡΠ°Π½ΠΈΡΠ΅Π½ΠΈΡ ΠΊΠ»Π°ΡΡΠ΅ΡΠΎΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ SNP-Π³Π΅Π½ΠΎΡΠΈΠΏΠΎΠ² ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ»ΠΈ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΡ ADMIXTURE. ΠΠΎ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ°ΠΌ MDS-Π°Π½Π°Π»ΠΈΠ·Π° ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½Π°Ρ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΡ Π±ΡΠ»Π° ΡΡΠ»ΠΎΠ²Π½ΠΎ ΡΠ°Π·Π΄Π΅Π»Π΅Π½Π° Π½Π° ΡΠ΅ΡΡΡΠ΅ MDS-Π³ΡΡΠΏΠΏΡ, ΡΡΠΎ Π² ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΈ Ρ Π΄Π°Π½Π½ΡΠΌΠΈ ΡΠΎΠ΄ΠΎΡΠ»ΠΎΠ²Π½ΠΎΠΉ Π°Π΄Π΅ΠΊΠ²Π°ΡΠ½ΠΎ ΠΎΡΡΠ°ΠΆΠ°Π΅Ρ ΠΏΡΠΎΠΈΡΡ
ΠΎΠΆΠ΄Π΅Π½ΠΈΠ΅ ΠΈΠ·ΡΡΠ΅Π½Π½ΡΡ
ΠΎΡΠΎΠ±Π΅ΠΉ. ΠΡΠ΅Π΄ΡΡΠ°Π²ΠΈΡΠ΅Π»ΠΈ ΠΏΡΠ΅Π΄ΠΊΠΎΠ²ΠΎΠΉ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ Π±ΡΠ»ΠΈ Π³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈ ΡΡ
ΠΎΠ΄Π½Ρ Ρ Π³ΡΡΠΏΠΏΠΎΠΉ MDS3. Π‘ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ F-ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ ΠΌΠ½ΠΎΠ³ΠΎΡΠ°ΠΊΡΠΎΡΠ½ΠΎΠ³ΠΎ Π΄ΠΈΡΠΏΠ΅ΡΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π²ΡΡΠ²Π»Π΅Π½ΠΎ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π³ΡΡΠΏΠΏΡ, Ρ
ΡΠΎΠΌΠΎΡΠΎΠΌΡ, Ρ
ΡΠΎΠΌΠΎΡΠΎΠΌΡ Π² Π³ΡΡΠΏΠΏΠ΅ ΠΈ Π΄ΠΈΡΡΠ°Π½ΡΠΈΠΈ ΠΌΠ΅ΠΆΠ΄Ρ SNP-ΠΌΠ°ΡΠΊΠ΅ΡΠ°ΠΌΠΈ Π½Π° Π·Π½Π°ΡΠ΅Π½ΠΈΡ LD (r2). Π Π³ΡΡΠΏΠΏΠ΅ 2001 Π³ΠΎΠ΄Π° ΠΏΠΎ Π²ΡΠ΅ΠΌ Ρ
ΡΠΎΠΌΠΎΡΠΎΠΌΠ°ΠΌ Π½Π°Π±Π»ΡΠ΄Π°Π»ΠΈΡΡ ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ r2 ΠΈ Π²ΡΡΠΎΠΊΠ°Ρ ΡΠ°ΡΡΠΎΡΠ° Π²ΡΡΡΠ΅ΡΠ°Π΅ΠΌΠΎΡΡΠΈ LD, ΡΠ°Π²Π½ΠΎΠ³ΠΎ 1, ΠΏΡΠΈ ΡΠ°ΡΡΡΠΎΡΠ½ΠΈΠΈ ΠΌΠ΅ΠΆΠ΄Ρ SNP-ΠΌΠ°ΡΠΊΠ΅ΡΠ°ΠΌΠΈ 500-1000 ΠΠ±. ΠΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΠΌΠΎΠ½ΠΎΠΌΠΎΡΡΠ½ΡΡ
Π°Π»Π»Π΅Π»Π΅ΠΉ Π² ΡΡΠΎΠΉ Π³ΡΡΠΏΠΏΠ΅ ΡΠ°ΠΊΠΆΠ΅ Π±ΡΠ»ΠΎ ΡΠ°ΠΌΡΠΌ Π²ΡΡΠΎΠΊΠΈΠΌ. ΠΠ° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ SNP-Π°Π½Π°Π»ΠΈΠ·Π° ΡΠ΄Π΅Π»Π°Π½ Π²ΡΠ²ΠΎΠ΄ ΠΎ ΡΠΎΠΌ, ΡΡΠΎ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½Π°Ρ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΡ ΡΡΡΡΠΊΠΈΡ
Π±Π΅Π»ΡΡ
ΠΊΡΡ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΠ΅ΡΡΡ ΡΠ°ΡΠΏΠ°Π΄ΠΎΠΌ Π΄Π»ΠΈΠ½Π½ΡΡ
LD-ΡΠ°ΠΉΠΎΠ½ΠΎΠ² ΠΏΡΠ΅Π΄ΠΊΠΎΠ²ΠΎΠΉ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ. ΠΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΊΠ»Π°ΡΡΠ΅ΡΠΎΠ² Π² ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ΅ ADMIXTURE Π²ΡΡΠ²ΠΈΠ»ΠΎ ΡΠ°Π·Π»ΠΈΡΠΈΡ ΠΌΠ΅ΠΆΠ΄Ρ Π³ΡΡΠΏΠΏΠ°ΠΌΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ, ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΠΌΠΈ Ρ ΠΏΠΎΠΌΠΎΡΡΡ MDS-Π°Π½Π°Π»ΠΈΠ·Π°. ΠΡΡΠΏΠΏΡ, ΡΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ ΠΈΠ· ΠΎΡΠΎΠ±Π΅ΠΉ, Π²Ρ
ΠΎΠ΄ΡΡΠΈΡ
Π² MDS1 ΠΈ MDS2, ΠΈΠΌΠ΅Π»ΠΈ ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΡ ΡΡΡΡΠΊΡΡΡΡ ΠΈ ΡΠ°Π·Π»ΠΈΡΠ°Π»ΠΈΡΡ ΠΌΠ΅ΠΆΠ΄Ρ ΡΠΎΠ±ΠΎΠΉ ΠΏΡΠΈ K = 4 ΠΈ K = 5. ΠΡΡΠΏΠΏΠ° MDS4 ΠΎΠ±ΡΠ°Π·ΠΎΠ²ΡΠ²Π°Π»Π° Π³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈ Π½Π΅ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΠΉ ΠΊΠ»Π°ΡΡΠ΅Ρ, ΠΎΡΠ»ΠΈΡΠ°ΡΡΠΈΠΉΡΡ ΠΎΡ Π³ΡΡΠΏΠΏ MDS1 ΠΈ MDS2 ΠΏΡΠΈ Π·Π½Π°ΡΠ΅Π½ΠΈΡΡ
K ΠΎΡ 2 Π΄ΠΎ 5. ΠΡΡΠΏΠΏΠ° MDS3 Π±ΡΠ»Π° ΡΠΈΠ»ΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈ Π±Π»ΠΈΠ·ΠΊΠ° ΠΊ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ 2001 Π³ΠΎΠ΄Π° (ΠΏΡΠΈ K ΠΎΡ 2 Π΄ΠΎ 5). Π’Π°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, Π°Π½Π°Π»ΠΈΠ· ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π³Π΅Π½ΠΎΡΠΎΠ½Π΄Π½ΠΎΠΉ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ ΡΡΡΡΠΊΠΈΡ
Π±Π΅Π»ΡΡ
ΠΊΡΡ ΠΏΠΎΠΊΠ°Π·Π°Π» Π΅Π΅ Π½Π΅ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΠΎΡΡΡ ΠΈ ΡΡ
ΠΎΠ΄ΡΡΠ²ΠΎ Π³ΡΡΠΏΠΏΡ MDS3 Ρ ΠΏΡΠ΅Π΄ΠΊΠΎΠ²ΠΎΠΉ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠ΅ΠΉ 2001 Π³ΠΎΠ΄Π°, ΠΊΠΎΡΠΎΡΠ°Ρ, Π² ΡΠ²ΠΎΡ ΠΎΡΠ΅ΡΠ΅Π΄Ρ, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΠΎΠ²Π°Π»Π°ΡΡ Π±ΠΎΠ»ΡΡΠΈΠΌ ΡΠΈΡΠ»ΠΎΠΌ ΠΌΠΎΠ½ΠΎΠΌΠΎΡΡΠ½ΡΡ
Π°Π»Π»Π΅Π»Π΅ΠΉ ΠΈ Π²ΡΡΠΎΠΊΠΎΠΉ ΡΠ°ΡΡΠΎΡΠΎΠΉ Π²ΡΡΡΠ΅ΡΠ°Π΅ΠΌΠΎΡΡΠΈ Π΄Π»ΠΈΠ½Π½ΡΡ
LD-ΡΠ°ΠΉΠΎΠ½ΠΎΠ². SNP-ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΠΎΡΠ΅Π½ΠΈΡΡ Π³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΡΡ
ΠΎΠ΄ΡΡΠ²ΠΎ ΠΎΡΠΎΠ±Π΅ΠΉ ΠΈ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΎΠ½Π½ΡΡ ΡΡΡΡΠΊΡΡΡΡ ΡΡΡΡΠΊΠΎΠΉ Π±Π΅Π»ΠΎΠΉ ΠΏΠΎΡΠΎΠ΄Ρ ΠΊΡΡ. ΠΠΎΠ½ΠΈΠΌΠ°Π½ΠΈΠ΅ Π³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΡΡΡΠΊΡΡΡΡ Π²Π°ΠΆΠ½ΠΎ ΠΏΡΠΈ ΠΏΠ°Π½ΠΌΠΈΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΌ ΡΠ°Π·Π²Π΅Π΄Π΅Π½ΠΈΠΈ ΠΈ ΠΎΡΡΠ»Π΅ΠΆΠΈΠ²Π°Π½ΠΈΠΈ ΠΈΡΡΠΎΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ Π² ΠΌΠΎΠ»Π΅ΠΊΡΠ»ΡΡΠ½ΠΎΠΉ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΈ Π³Π΅Π½ΠΎΠΌΠ° Π³Π΅Π½ΠΎΡΠΎΠ½Π΄Π½ΠΎΠΉ ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ Ρ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΠΌ ΠΏΠΎΠ³ΠΎΠ»ΠΎΠ²ΡΠ΅ΠΌ